diff --git a/Exercise1/exercise1.ipynb b/Exercise1/exercise1.ipynb
index 7ebc6fa0..fddf8450 100755
--- a/Exercise1/exercise1.ipynb
+++ b/Exercise1/exercise1.ipynb
@@ -19,7 +19,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -108,7 +108,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -126,7 +126,7 @@
     "    Return the 5x5 identity matrix.\n",
     "    \"\"\"    \n",
     "    # ======== YOUR CODE HERE ======\n",
-    "    A = []   # modify this line\n",
+    "    A = np.eye(5)  # modify this line\n",
     "    \n",
     "    # ==============================\n",
     "    return A"
@@ -149,9 +149,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 1.,  0.,  0.,  0.,  0.],\n",
+       "       [ 0.,  1.,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  1.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0.,  1.,  0.],\n",
+       "       [ 0.,  0.,  0.,  0.,  1.]])"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "warmUpExercise()"
    ]
@@ -173,9 +188,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise linear-regression\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): \n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "                           Warm up exercise |  10 /  10 | Nice work!\n",
+      "          Computing Cost (for one variable) |   0 /  40 | \n",
+      "        Gradient Descent (for one variable) |   0 /  50 | \n",
+      "                      Feature Normalization |   0 /   0 | \n",
+      "    Computing Cost (for multiple variables) |   0 /   0 | \n",
+      "  Gradient Descent (for multiple variables) |   0 /   0 | \n",
+      "                           Normal Equations |   0 /   0 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  10 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "# appends the implemented function in part 1 to the grader object\n",
     "grader[1] = warmUpExercise\n",
@@ -199,15 +237,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "97"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Read comma separated data\n",
     "data = np.loadtxt(os.path.join('Data', 'ex1data1.txt'), delimiter=',')\n",
     "X, y = data[:, 0], data[:, 1]\n",
     "\n",
-    "m = y.size  # number of training examples"
+    "m = y.size  # number of training examples\n",
+    "m"
    ]
   },
   {
@@ -236,7 +286,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -268,9 +318,11 @@
     "    can also set the marker edge color using the `mec` property.\n",
     "    \"\"\"\n",
     "    fig = pyplot.figure()  # open a new figure\n",
-    "    \n",
+    "\n",
     "    # ====================== YOUR CODE HERE ======================= \n",
-    "    \n",
+    "    pyplot.plot(x, y, 'ro', ms=10)\n",
+    "    pyplot.xlabel('City Population in 10,000s')\n",
+    "    pyplot.ylabel('Profit in $10,000s')\n",
     "\n",
     "    # =============================================================\n"
    ]
@@ -288,9 +340,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff7c06e60f0>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plotData(X, y)"
    ]
@@ -306,7 +371,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -352,7 +417,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -375,13 +440,56 @@
     "<a id=\"computeCost\"></a>"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Compute hypothesis function"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def computeHypothesis(X, theta):\n",
+    "    thetaT = theta.transpose()\n",
+    "    return X @ thetaT"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def computeCost_loop(X, y, theta):\n",
+    "    m = y.size  # number of training examples\n",
+    "    # You need to return the following variables correctly\n",
+    "    J = 0\n",
+    "    \n",
+    "    # ====================== YOUR CODE HERE =====================\n",
+    "    def cost_loop(hypothesis, m, y):\n",
+    "        summation = 0\n",
+    "        for i in range(m):\n",
+    "            squared_error = (hypothesis[i] - y[i])**2\n",
+    "            summation += squared_error\n",
+    "        return summation\n",
+    "    \n",
+    "    hypothesis = computeHypothesis(X, theta)\n",
+    "    summation = cost_loop(hypothesis, m, y)\n",
+    "    J = summation / (2*m) \n",
+    "    return J"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
    "metadata": {},
    "outputs": [],
    "source": [
-    "def computeCost(X, y, theta):\n",
+    "def computeCost_vectorized(X, y, theta):\n",
     "    \"\"\"\n",
     "    Compute cost for linear regression. Computes the cost of using theta as the\n",
     "    parameter for linear regression to fit the data points in X and y.\n",
@@ -411,7 +519,7 @@
     "    Compute the cost of a particular choice of theta. \n",
     "    You should set J to the cost.\n",
     "    \"\"\"\n",
-    "    \n",
+    "\n",
     "    # initialize some useful values\n",
     "    m = y.size  # number of training examples\n",
     "    \n",
@@ -419,31 +527,116 @@
     "    J = 0\n",
     "    \n",
     "    # ====================== YOUR CODE HERE =====================\n",
-    "\n",
+    "    def cost_vectorized(hypothesis, y):\n",
+    "        error = np.subtract(hypothesis, y)\n",
+    "        squared_error = np.square(error)\n",
+    "        summation = np.sum(squared_error)\n",
+    "        return summation\n",
     "    \n",
-    "    # ===========================================================\n",
-    "    return J"
+    "    hypothesis = computeHypothesis(X, theta)\n",
+    "    summation = cost_vectorized(hypothesis, y)\n",
+    "    J = summation / (2*m) \n",
+    "    return J "
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Once you have completed the function, the next step will run `computeCost` two times using two different initializations of $\\theta$. You will see the cost printed to the screen."
+    "Compare between for loop vs vectorized numpy implementation for cost function"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 43,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 580 µs, sys: 76 µs, total: 656 µs\n",
+      "Wall time: 424 µs\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "32.072733877455654"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%time computeCost_loop(X, y, theta=np.array([0.0, 0.0]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 638 µs, sys: 83 µs, total: 721 µs\n",
+      "Wall time: 464 µs\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "32.072733877455676"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%time computeCost_vectorized(X, y, theta=np.array([0.0, 0.0]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "J = computeCost(X, y, theta=np.array([0.0, 0.0]))\n",
+    "Once you have completed the function, the next step will run `computeCost` two times using two different initializations of $\\theta$. You will see the cost printed to the screen."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "With theta = [0, 0] \n",
+      "Cost computed = 32.07\n",
+      "Expected cost value (approximately) 32.07\n",
+      "\n",
+      "With theta = [-1, 2]\n",
+      "Cost computed = 54.24\n",
+      "Expected cost value (approximately) 54.24\n"
+     ]
+    }
+   ],
+   "source": [
+    "J = computeCost_vectorized(X, y, theta=np.array([0.0, 0.0]))\n",
     "print('With theta = [0, 0] \\nCost computed = %.2f' % J)\n",
     "print('Expected cost value (approximately) 32.07\\n')\n",
     "\n",
     "# further testing of the cost function\n",
-    "J = computeCost(X, y, theta=np.array([-1, 2]))\n",
+    "J = computeCost_vectorized(X, y, theta=np.array([-1, 2]))\n",
     "print('With theta = [-1, 2]\\nCost computed = %.2f' % J)\n",
     "print('Expected cost value (approximately) 54.24')"
    ]
@@ -457,11 +650,34 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "grader[2] = computeCost\n",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise linear-regression\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): \n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "                           Warm up exercise |  10 /  10 | Nice work!\n",
+      "          Computing Cost (for one variable) |  40 /  40 | Nice work!\n",
+      "        Gradient Descent (for one variable) |   0 /  50 | \n",
+      "                      Feature Normalization |   0 /   0 | \n",
+      "    Computing Cost (for multiple variables) |   0 /   0 | \n",
+      "  Gradient Descent (for multiple variables) |   0 /   0 | \n",
+      "                           Normal Equations |   0 /   0 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  50 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "grader[2] = computeCost_vectorized\n",
     "grader.grade()"
    ]
   },
@@ -494,7 +710,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -544,15 +760,26 @@
     "    theta = theta.copy()\n",
     "    \n",
     "    J_history = [] # Use a python list to save cost in every iteration\n",
-    "    \n",
+    "    n = theta.shape[0]\n",
     "    for i in range(num_iters):\n",
     "        # ==================== YOUR CODE HERE =================================\n",
-    "        \n",
-    "\n",
+    "        theta_temp = theta.copy()\n",
+    "        for j in range(n):\n",
+    "            hypothesis = computeHypothesis(X, theta)\n",
+    "            summation = 0\n",
+    "            error = np.subtract(hypothesis, y)\n",
+    "            error_by_xOfj = error @ X[:, j]\n",
+    "            summation = np.sum(error_by_xOfj)\n",
+    "            gradient = (alpha * summation) / m\n",
+    "            theta_temp[j] -= gradient\n",
+    "            \n",
+    "        theta = theta_temp\n",
+    "        J = computeCost_vectorized(X, y, theta)\n",
+    "        print(\"Cost function: {}\".format(J))\n",
     "        # =====================================================================\n",
     "        \n",
     "        # save the cost J in every iteration\n",
-    "        J_history.append(computeCost(X, y, theta))\n",
+    "        J_history.append(J)\n",
     "    \n",
     "    return theta, J_history"
    ]
@@ -566,9 +793,1536 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cost function: 6.737190464870008\n",
+      "Cost function: 5.931593568604956\n",
+      "Cost function: 5.901154707081388\n",
+      "Cost function: 5.895228586444221\n",
+      "Cost function: 5.8900949431173295\n",
+      "Cost function: 5.885004158443647\n",
+      "Cost function: 5.879932480491418\n",
+      "Cost function: 5.874879094762575\n",
+      "Cost function: 5.869843911806385\n",
+      "Cost function: 5.8648268653129305\n",
+      "Cost function: 5.859827889932181\n",
+      "Cost function: 5.85484692057229\n",
+      "Cost function: 5.849883892376587\n",
+      "Cost function: 5.844938740722034\n",
+      "Cost function: 5.840011401218361\n",
+      "Cost function: 5.835101809707226\n",
+      "Cost function: 5.830209902261388\n",
+      "Cost function: 5.825335615183863\n",
+      "Cost function: 5.820478885007099\n",
+      "Cost function: 5.815639648492154\n",
+      "Cost function: 5.810817842627869\n",
+      "Cost function: 5.806013404630044\n",
+      "Cost function: 5.801226271940628\n",
+      "Cost function: 5.7964563822269\n",
+      "Cost function: 5.7917036733806535\n",
+      "Cost function: 5.7869680835173956\n",
+      "Cost function: 5.782249550975539\n",
+      "Cost function: 5.777548014315596\n",
+      "Cost function: 5.772863412319381\n",
+      "Cost function: 5.768195683989212\n",
+      "Cost function: 5.76354476854712\n",
+      "Cost function: 5.758910605434047\n",
+      "Cost function: 5.754293134309077\n",
+      "Cost function: 5.749692295048629\n",
+      "Cost function: 5.745108027745684\n",
+      "Cost function: 5.740540272709012\n",
+      "Cost function: 5.735988970462381\n",
+      "Cost function: 5.731454061743792\n",
+      "Cost function: 5.726935487504702\n",
+      "Cost function: 5.722433188909257\n",
+      "Cost function: 5.717947107333529\n",
+      "Cost function: 5.713477184364749\n",
+      "Cost function: 5.709023361800549\n",
+      "Cost function: 5.704585581648199\n",
+      "Cost function: 5.700163786123857\n",
+      "Cost function: 5.695757917651815\n",
+      "Cost function: 5.691367918863752\n",
+      "Cost function: 5.68699373259798\n",
+      "Cost function: 5.682635301898707\n",
+      "Cost function: 5.678292570015292\n",
+      "Cost function: 5.673965480401506\n",
+      "Cost function: 5.669653976714796\n",
+      "Cost function: 5.6653580028155535\n",
+      "Cost function: 5.661077502766379\n",
+      "Cost function: 5.6568124208313595\n",
+      "Cost function: 5.6525627014753335\n",
+      "Cost function: 5.648328289363181\n",
+      "Cost function: 5.644109129359092\n",
+      "Cost function: 5.639905166525854\n",
+      "Cost function: 5.635716346124135\n",
+      "Cost function: 5.631542613611772\n",
+      "Cost function: 5.627383914643055\n",
+      "Cost function: 5.623240195068026\n",
+      "Cost function: 5.619111400931778\n",
+      "Cost function: 5.61499747847374\n",
+      "Cost function: 5.610898374126984\n",
+      "Cost function: 5.606814034517531\n",
+      "Cost function: 5.602744406463646\n",
+      "Cost function: 5.598689436975159\n",
+      "Cost function: 5.59464907325276\n",
+      "Cost function: 5.590623262687323\n",
+      "Cost function: 5.586611952859217\n",
+      "Cost function: 5.5826150915376225\n",
+      "Cost function: 5.578632626679853\n",
+      "Cost function: 5.574664506430678\n",
+      "Cost function: 5.570710679121643\n",
+      "Cost function: 5.566771093270403\n",
+      "Cost function: 5.562845697580051\n",
+      "Cost function: 5.558934440938442\n",
+      "Cost function: 5.555037272417543\n",
+      "Cost function: 5.551154141272754\n",
+      "Cost function: 5.547284996942256\n",
+      "Cost function: 5.5434297890463515\n",
+      "Cost function: 5.539588467386808\n",
+      "Cost function: 5.535760981946204\n",
+      "Cost function: 5.531947282887275\n",
+      "Cost function: 5.5281473205522715\n",
+      "Cost function: 5.524361045462306\n",
+      "Cost function: 5.520588408316713\n",
+      "Cost function: 5.5168293599924025\n",
+      "Cost function: 5.513083851543225\n",
+      "Cost function: 5.5093518341993315\n",
+      "Cost function: 5.5056332593665385\n",
+      "Cost function: 5.501928078625699\n",
+      "Cost function: 5.498236243732065\n",
+      "Cost function: 5.494557706614666\n",
+      "Cost function: 5.490892419375677\n",
+      "Cost function: 5.487240334289805\n",
+      "Cost function: 5.483601403803652\n",
+      "Cost function: 5.479975580535112\n",
+      "Cost function: 5.476362817272741\n",
+      "Cost function: 5.472763066975151\n",
+      "Cost function: 5.469176282770398\n",
+      "Cost function: 5.465602417955358\n",
+      "Cost function: 5.462041425995137\n",
+      "Cost function: 5.4584932605224585\n",
+      "Cost function: 5.454957875337047\n",
+      "Cost function: 5.451435224405051\n",
+      "Cost function: 5.4479252618584235\n",
+      "Cost function: 5.444427941994333\n",
+      "Cost function: 5.440943219274565\n",
+      "Cost function: 5.437471048324934\n",
+      "Cost function: 5.434011383934687\n",
+      "Cost function: 5.430564181055919\n",
+      "Cost function: 5.427129394802985\n",
+      "Cost function: 5.423706980451918\n",
+      "Cost function: 5.420296893439836\n",
+      "Cost function: 5.416899089364381\n",
+      "Cost function: 5.413513523983123\n",
+      "Cost function: 5.4101401532129865\n",
+      "Cost function: 5.406778933129694\n",
+      "Cost function: 5.403429819967165\n",
+      "Cost function: 5.400092770116975\n",
+      "Cost function: 5.396767740127768\n",
+      "Cost function: 5.393454686704697\n",
+      "Cost function: 5.390153566708862\n",
+      "Cost function: 5.386864337156747\n",
+      "Cost function: 5.383586955219661\n",
+      "Cost function: 5.380321378223178\n",
+      "Cost function: 5.37706756364658\n",
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+      "Cost function: 4.491216268705828\n",
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+      "Cost function: 4.490514516826771\n",
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+      "Cost function: 4.486480508053741\n",
+      "Cost function: 4.486446256708757\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cost function: 4.486412128735142\n",
+      "Cost function: 4.486378123688517\n",
+      "Cost function: 4.486344241126109\n",
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+      "Cost function: 4.486110455887582\n",
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+      "Cost function: 4.484574270430969\n",
+      "Cost function: 4.484546885243894\n",
+      "Cost function: 4.484519598696685\n",
+      "Cost function: 4.484492410434043\n",
+      "Cost function: 4.484465320101953\n",
+      "Cost function: 4.484438327347678\n",
+      "Cost function: 4.484411431819744\n",
+      "Cost function: 4.484384633167951\n",
+      "Cost function: 4.484357931043356\n",
+      "Cost function: 4.484331325098271\n",
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+      "Cost function: 4.484278400362154\n",
+      "Cost function: 4.484252080881994\n",
+      "Cost function: 4.484225856203082\n",
+      "Cost function: 4.4841997259839514\n",
+      "Cost function: 4.4841736898843605\n",
+      "Cost function: 4.484147747565299\n",
+      "Cost function: 4.484121898688972\n",
+      "Cost function: 4.4840961429188075\n",
+      "Cost function: 4.48407047991944\n",
+      "Cost function: 4.484044909356716\n",
+      "Cost function: 4.484019430897683\n",
+      "Cost function: 4.483994044210589\n",
+      "Cost function: 4.483968748964877\n",
+      "Cost function: 4.483943544831179\n",
+      "Cost function: 4.483918431481319\n",
+      "Cost function: 4.483893408588292\n",
+      "Cost function: 4.483868475826285\n",
+      "Cost function: 4.483843632870647\n",
+      "Cost function: 4.483818879397901\n",
+      "Cost function: 4.4837942150857355\n",
+      "Cost function: 4.483769639613\n",
+      "Cost function: 4.483745152659696\n",
+      "Cost function: 4.483720753906987\n",
+      "Cost function: 4.483696443037178\n",
+      "Cost function: 4.483672219733719\n",
+      "Cost function: 4.483648083681199\n",
+      "Cost function: 4.483624034565349\n",
+      "Cost function: 4.483600072073026\n",
+      "Cost function: 4.483576195892218\n",
+      "Cost function: 4.483552405712033\n",
+      "Cost function: 4.483528701222708\n",
+      "Cost function: 4.483505082115583\n",
+      "Cost function: 4.48348154808312\n",
+      "Cost function: 4.483458098818883\n",
+      "Cost function: 4.483434734017543\n",
+      "Cost function: 4.483411453374869\n",
+      "Cost function: 4.483388256587726\n",
+      "Theta found by gradient descent: -3.6303, 1.1664\n",
+      "Expected theta values (approximately): [-3.6303, 1.1664]\n"
+     ]
+    }
+   ],
    "source": [
     "# initialize fitting parameters\n",
     "theta = np.zeros(2)\n",
@@ -593,9 +2347,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff7c0192ef0>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# plot the linear fit\n",
     "plotData(X[:, 1], y)\n",
@@ -620,9 +2387,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "For population = 35,000, we predict a profit of 4519.77\n",
+      "\n",
+      "For population = 70,000, we predict a profit of 45342.45\n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "# Predict values for population sizes of 35,000 and 70,000\n",
     "predict1 = np.dot([1, 3.5], theta)\n",
@@ -641,9 +2419,42 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise linear-regression\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "Cost function: 12.492645519866524\n",
+      "Cost function: 1.2598100268044834\n",
+      "Cost function: 0.32964276347930116\n",
+      "Cost function: 0.2525997665089539\n",
+      "Cost function: 0.2462007536884619\n",
+      "Cost function: 0.24565155127262028\n",
+      "Cost function: 0.24558680353659232\n",
+      "Cost function: 0.24556222591736288\n",
+      "Cost function: 0.24554102877121778\n",
+      "Cost function: 0.24552016553714492\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "                           Warm up exercise |  10 /  10 | Nice work!\n",
+      "          Computing Cost (for one variable) |  40 /  40 | Nice work!\n",
+      "        Gradient Descent (for one variable) |  50 /  50 | Nice work!\n",
+      "                      Feature Normalization |   0 /   0 | \n",
+      "    Computing Cost (for multiple variables) |   0 /   0 | \n",
+      "  Gradient Descent (for multiple variables) |   0 /   0 | \n",
+      "                           Normal Equations |   0 /   0 | \n",
+      "                                  --------------------------------\n",
+      "                                            | 100 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[3] = gradientDescent\n",
     "grader.grade()"
@@ -666,9 +2477,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff7c00d8f28>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# grid over which we will calculate J\n",
     "theta0_vals = np.linspace(-10, 10, 100)\n",
@@ -680,7 +2504,7 @@
     "# Fill out J_vals\n",
     "for i, theta0 in enumerate(theta0_vals):\n",
     "    for j, theta1 in enumerate(theta1_vals):\n",
-    "        J_vals[i, j] = computeCost(X, y, [theta0, theta1])\n",
+    "        J_vals[i, j] = computeCost_vectorized(X, y, np.array([theta0, theta1]))\n",
     "        \n",
     "# Because of the way meshgrids work in the surf command, we need to\n",
     "# transpose J_vals before calling surf, or else the axes will be flipped\n",
@@ -730,9 +2554,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 99,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "  X[:,0] X[:, 1]         y\n",
+      "--------------------------\n",
+      "    2104       3    399900\n",
+      "    1600       3    329900\n",
+      "    2400       3    369000\n",
+      "    1416       2    232000\n",
+      "    3000       4    539900\n",
+      "    1985       4    299900\n",
+      "    1534       3    314900\n",
+      "    1427       3    198999\n",
+      "    1380       3    212000\n",
+      "    1494       3    242500\n"
+     ]
+    }
+   ],
    "source": [
     "# Load data\n",
     "data = np.loadtxt(os.path.join('Data', 'ex1data2.txt'), delimiter=',')\n",
@@ -773,7 +2616,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 100,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -815,8 +2658,14 @@
     "    sigma = np.zeros(X.shape[1])\n",
     "\n",
     "    # =========================== YOUR CODE HERE =====================\n",
+    "    for j in range(X_norm.shape[1]):\n",
+    "        mu[j] = np.mean(X_norm[:, j])\n",
+    "        print(\"mean {0}: {1}\".format(j, mu[j]))\n",
+    "        sigma[j] = np.std(X_norm[:, j])\n",
+    "        print(\"sigma {0}: {1}\".format(j, sigma[j]))\n",
+    "\n",
+    "    X_norm = np.divide(np.subtract(X_norm, mu), sigma)\n",
     "\n",
-    "    \n",
     "    # ================================================================\n",
     "    return X_norm, mu, sigma"
    ]
@@ -830,9 +2679,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 101,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "mean 0: 2000.6808510638298\n",
+      "sigma 0: 786.2026187430467\n",
+      "mean 1: 3.1702127659574466\n",
+      "sigma 1: 0.7528428090618781\n",
+      "Computed mean: [ 2000.68085106     3.17021277]\n",
+      "Computed standard deviation: [  7.86202619e+02   7.52842809e-01]\n"
+     ]
+    }
+   ],
    "source": [
     "# call featureNormalize on the loaded data\n",
     "X_norm, mu, sigma = featureNormalize(X)\n",
@@ -850,9 +2712,58 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 102,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise linear-regression\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): \n",
+      "Cost function: 12.492645519866524\n",
+      "Cost function: 1.2598100268044834\n",
+      "Cost function: 0.32964276347930116\n",
+      "Cost function: 0.2525997665089539\n",
+      "Cost function: 0.2462007536884619\n",
+      "Cost function: 0.24565155127262028\n",
+      "Cost function: 0.24558680353659232\n",
+      "Cost function: 0.24556222591736288\n",
+      "Cost function: 0.24554102877121778\n",
+      "Cost function: 0.24552016553714492\n",
+      "mean 0: 10.47679073233623\n",
+      "sigma 0: 4.260737598822586\n",
+      "mean 1: 3.162121914331882\n",
+      "sigma 1: 0.6912132313825448\n",
+      "mean 2: 1.7669307220546364\n",
+      "sigma 2: 0.2001942501456096\n",
+      "Cost function: 33.624038110459594\n",
+      "Cost function: 6.576615712126629\n",
+      "Cost function: 1.8163913328722827\n",
+      "Cost function: 0.9745349470582501\n",
+      "Cost function: 0.8216274270702817\n",
+      "Cost function: 0.7899048213339446\n",
+      "Cost function: 0.7795479644437096\n",
+      "Cost function: 0.7730069291657166\n",
+      "Cost function: 0.7671955270326364\n",
+      "Cost function: 0.7615704442641105\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "                           Warm up exercise |  10 /  10 | Nice work!\n",
+      "          Computing Cost (for one variable) |  40 /  40 | Nice work!\n",
+      "        Gradient Descent (for one variable) |  50 /  50 | Nice work!\n",
+      "                      Feature Normalization |   0 /   0 | Nice work!\n",
+      "    Computing Cost (for multiple variables) |   0 /   0 | Nice work!\n",
+      "  Gradient Descent (for multiple variables) |   0 /   0 | Nice work!\n",
+      "                           Normal Equations |   0 /   0 | \n",
+      "                                  --------------------------------\n",
+      "                                            | 100 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[4] = featureNormalize\n",
     "grader.grade()"
@@ -867,12 +2778,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 103,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "  X[:,0] X[:, 1] X[:, 2]         y\n",
+      "--------------------------\n",
+      "       1       0      -0    399900\n",
+      "       1      -1      -0    329900\n",
+      "       1       1      -0    369000\n",
+      "       1      -1      -2    232000\n",
+      "       1       1       1    539900\n",
+      "       1      -0       1    299900\n",
+      "       1      -1      -0    314900\n",
+      "       1      -1      -0    198999\n",
+      "       1      -1      -0    212000\n",
+      "       1      -1      -0    242500\n"
+     ]
+    }
+   ],
    "source": [
     "# Add intercept term to X\n",
-    "X = np.concatenate([np.ones((m, 1)), X_norm], axis=1)"
+    "X = np.concatenate([np.ones((m, 1)), X_norm], axis=1)\n",
+    "print('{:>8s}{:>8s}{:>8s}{:>10s}'.format('X[:,0]', 'X[:, 1]', 'X[:, 2]','y'))\n",
+    "print('-'*26)\n",
+    "for i in range(10):\n",
+    "    print('{:8.0f}{:8.0f}{:8.0f}{:10.0f}'.format(X[i, 0], X[i, 1], X[i, 2], y[i]))"
    ]
   },
   {
@@ -912,7 +2846,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 104,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -948,7 +2882,7 @@
     "    J = 0\n",
     "    \n",
     "    # ======================= YOUR CODE HERE ===========================\n",
-    "\n",
+    "    J = computeCost_vectorized(X, y, theta)\n",
     "    \n",
     "    # ==================================================================\n",
     "    return J\n"
@@ -963,9 +2897,58 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 105,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise linear-regression\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): \n",
+      "Cost function: 12.492645519866524\n",
+      "Cost function: 1.2598100268044834\n",
+      "Cost function: 0.32964276347930116\n",
+      "Cost function: 0.2525997665089539\n",
+      "Cost function: 0.2462007536884619\n",
+      "Cost function: 0.24565155127262028\n",
+      "Cost function: 0.24558680353659232\n",
+      "Cost function: 0.24556222591736288\n",
+      "Cost function: 0.24554102877121778\n",
+      "Cost function: 0.24552016553714492\n",
+      "mean 0: 10.47679073233623\n",
+      "sigma 0: 4.260737598822586\n",
+      "mean 1: 3.162121914331882\n",
+      "sigma 1: 0.6912132313825448\n",
+      "mean 2: 1.7669307220546364\n",
+      "sigma 2: 0.2001942501456096\n",
+      "Cost function: 33.624038110459594\n",
+      "Cost function: 6.576615712126629\n",
+      "Cost function: 1.8163913328722827\n",
+      "Cost function: 0.9745349470582501\n",
+      "Cost function: 0.8216274270702817\n",
+      "Cost function: 0.7899048213339446\n",
+      "Cost function: 0.7795479644437096\n",
+      "Cost function: 0.7730069291657166\n",
+      "Cost function: 0.7671955270326364\n",
+      "Cost function: 0.7615704442641105\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "                           Warm up exercise |  10 /  10 | Nice work!\n",
+      "          Computing Cost (for one variable) |  40 /  40 | Nice work!\n",
+      "        Gradient Descent (for one variable) |  50 /  50 | Nice work!\n",
+      "                      Feature Normalization |   0 /   0 | Nice work!\n",
+      "    Computing Cost (for multiple variables) |   0 /   0 | Nice work!\n",
+      "  Gradient Descent (for multiple variables) |   0 /   0 | Nice work!\n",
+      "                           Normal Equations |   0 /   0 | \n",
+      "                                  --------------------------------\n",
+      "                                            | 100 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[5] = computeCostMulti\n",
     "grader.grade()"
@@ -980,7 +2963,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 106,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1028,10 +3011,22 @@
     "    theta = theta.copy()\n",
     "    \n",
     "    J_history = []\n",
-    "    \n",
+    "    n = theta.shape[0]\n",
     "    for i in range(num_iters):\n",
     "        # ======================= YOUR CODE HERE ==========================\n",
-    "\n",
+    "        theta_temp = theta.copy()\n",
+    "        for j in range(n):\n",
+    "            hypothesis = computeHypothesis(X, theta)\n",
+    "            summation = 0\n",
+    "            error = np.subtract(hypothesis, y)\n",
+    "            error_by_xOfj = error @ X[:, j]\n",
+    "            summation = np.sum(error_by_xOfj)\n",
+    "            gradient = (alpha * summation) / m\n",
+    "            theta_temp[j] -= gradient\n",
+    "            \n",
+    "        theta = theta_temp\n",
+    "        J = computeCost_vectorized(X, y, theta)\n",
+    "        print(\"Cost function: {}\".format(J))\n",
     "        \n",
     "        # =================================================================\n",
     "        \n",
@@ -1050,9 +3045,58 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 107,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise linear-regression\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): \n",
+      "Cost function: 12.492645519866524\n",
+      "Cost function: 1.2598100268044834\n",
+      "Cost function: 0.32964276347930116\n",
+      "Cost function: 0.2525997665089539\n",
+      "Cost function: 0.2462007536884619\n",
+      "Cost function: 0.24565155127262028\n",
+      "Cost function: 0.24558680353659232\n",
+      "Cost function: 0.24556222591736288\n",
+      "Cost function: 0.24554102877121778\n",
+      "Cost function: 0.24552016553714492\n",
+      "mean 0: 10.47679073233623\n",
+      "sigma 0: 4.260737598822586\n",
+      "mean 1: 3.162121914331882\n",
+      "sigma 1: 0.6912132313825448\n",
+      "mean 2: 1.7669307220546364\n",
+      "sigma 2: 0.2001942501456096\n",
+      "Cost function: 33.624038110459594\n",
+      "Cost function: 6.576615712126629\n",
+      "Cost function: 1.8163913328722827\n",
+      "Cost function: 0.9745349470582501\n",
+      "Cost function: 0.8216274270702817\n",
+      "Cost function: 0.7899048213339446\n",
+      "Cost function: 0.7795479644437096\n",
+      "Cost function: 0.7730069291657166\n",
+      "Cost function: 0.7671955270326364\n",
+      "Cost function: 0.7615704442641105\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "                           Warm up exercise |  10 /  10 | Nice work!\n",
+      "          Computing Cost (for one variable) |  40 /  40 | Nice work!\n",
+      "        Gradient Descent (for one variable) |  50 /  50 | Nice work!\n",
+      "                      Feature Normalization |   0 /   0 | Nice work!\n",
+      "    Computing Cost (for multiple variables) |   0 /   0 | Nice work!\n",
+      "  Gradient Descent (for multiple variables) |   0 /   0 | Nice work!\n",
+      "                           Normal Equations |   0 /   0 | \n",
+      "                                  --------------------------------\n",
+      "                                            | 100 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[6] = gradientDescentMulti\n",
     "grader.grade()"
@@ -1082,7 +3126,7 @@
     "</div>\n",
     "\n",
     "<div class=\"alert alert-block alert-warning\">\n",
-    "**MATPLOTLIB tip:** To compare how different learning learning rates affect convergence, it is helpful to plot $J$ for several learning rates on the same figure. This can be done by making `alpha` a python list, and looping across the values within this list, and calling the plot function in every iteration of the loop. It is also useful to have a legend to distinguish the different lines within the plot. Search online for `pyplot.legend` for help on showing legends in `matplotlib`.\n",
+    "**MATPLOTLIB tip:** To compare how different learning rates affect convergence, it is helpful to plot $J$ for several learning rates on the same figure. This can be done by making `alpha` a python list, and looping across the values within this list, and calling the plot function in every iteration of the loop. It is also useful to have a legend to distinguish the different lines within the plot. Search online for `pyplot.legend` for help on showing legends in `matplotlib`.\n",
     "</div>\n",
     "\n",
     "Notice the changes in the convergence curves as the learning rate changes. With a small learning rate, you should find that gradient descent takes a very long time to converge to the optimal value. Conversely, with a large learning rate, gradient descent might not converge or might even diverge!\n",
@@ -1094,9 +3138,80 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 122,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cost function: 53268259941.69158\n",
+      "Cost function: 43389084347.20148\n",
+      "Cost function: 35457430400.18726\n",
+      "Cost function: 29080554650.26538\n",
+      "Cost function: 23947078942.486904\n",
+      "Cost function: 19809572950.407112\n",
+      "Cost function: 16471010836.840017\n",
+      "Cost function: 13774203352.014154\n",
+      "Cost function: 11593524216.527594\n",
+      "Cost function: 9828412382.488955\n",
+      "Cost function: 8398254002.783358\n",
+      "Cost function: 7238340120.371357\n",
+      "Cost function: 6296665891.9603405\n",
+      "Cost function: 5531390234.906865\n",
+      "Cost function: 4908815308.044031\n",
+      "Cost function: 4401776301.436806\n",
+      "Cost function: 3988355919.6420965\n",
+      "Cost function: 3650856417.631556\n",
+      "Cost function: 3374976377.455051\n",
+      "Cost function: 3149150567.4992957\n",
+      "Cost function: 2964019938.3496037\n",
+      "Cost function: 2812005636.475741\n",
+      "Cost function: 2686966283.4586883\n",
+      "Cost function: 2583921998.861997\n",
+      "Cost function: 2498831988.5192094\n",
+      "Cost function: 2428415169.31641\n",
+      "Cost function: 2370005405.4349537\n",
+      "Cost function: 2321434605.2294416\n",
+      "Cost function: 2280938262.7171597\n",
+      "Cost function: 2247079093.6803536\n",
+      "Cost function: 2218685269.0753884\n",
+      "Cost function: 2194800431.452254\n",
+      "Cost function: 2174643227.872602\n",
+      "Cost function: 2157574532.6463156\n",
+      "Cost function: 2143070886.7210467\n",
+      "Cost function: 2130702964.9561472\n",
+      "Cost function: 2120118111.493527\n",
+      "Cost function: 2111026167.9366653\n",
+      "Cost function: 2103187967.8047752\n",
+      "Cost function: 2096405990.737132\n",
+      "Cost function: 2090516766.7901177\n",
+      "Cost function: 2085384699.395915\n",
+      "Cost function: 2080897038.7516391\n",
+      "Cost function: 2076959788.4875047\n",
+      "Cost function: 2073494369.7613983\n",
+      "Cost function: 2070434900.3288796\n",
+      "Cost function: 2067725973.1604218\n",
+      "Cost function: 2065320841.0460682\n",
+      "Cost function: 2063179931.329474\n",
+      "Cost function: 2061269629.2461314\n",
+      "theta computed from gradient descent: [ 338658.2492493   103322.82942954    -474.74249522]\n",
+      "Predicted price of a 1650 sq-ft, 3 br house (using gradient descent): $292679\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff7b2ae84a8>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "\"\"\"\n",
     "Instructions\n",
@@ -1120,7 +3235,7 @@
     "\"\"\"\n",
     "# Choose some alpha value - change this\n",
     "alpha = 0.1\n",
-    "num_iters = 400\n",
+    "num_iters = 50\n",
     "\n",
     "# init theta and run gradient descent\n",
     "theta = np.zeros(3)\n",
@@ -1139,7 +3254,10 @@
     "# Recall that the first column of X is all-ones. \n",
     "# Thus, it does not need to be normalized.\n",
     "\n",
-    "price = 0   # You should change this\n",
+    "feature1_normalized = (1650 - mu[0]) / sigma[0]\n",
+    "feature2_normalized = (3 - mu[1]) / sigma[1]\n",
+    "\n",
+    "price = np.dot([1, feature1_normalized, feature2_normalized], theta)\n",
     "\n",
     "# ===================================================================\n",
     "\n",
@@ -1171,7 +3289,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 123,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1194,7 +3312,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 124,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1225,9 +3343,8 @@
     "    Look up the function `np.linalg.pinv` for computing matrix inverse.\n",
     "    \"\"\"\n",
     "    theta = np.zeros(X.shape[1])\n",
-    "    \n",
     "    # ===================== YOUR CODE HERE ============================\n",
-    "\n",
+    "    theta = ((np.linalg.pinv(X.T @ X)) @ X.T) @ y\n",
     "    \n",
     "    # =================================================================\n",
     "    return theta"
@@ -1242,9 +3359,58 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 125,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise linear-regression\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): \n",
+      "Cost function: 12.492645519866524\n",
+      "Cost function: 1.2598100268044834\n",
+      "Cost function: 0.32964276347930116\n",
+      "Cost function: 0.2525997665089539\n",
+      "Cost function: 0.2462007536884619\n",
+      "Cost function: 0.24565155127262028\n",
+      "Cost function: 0.24558680353659232\n",
+      "Cost function: 0.24556222591736288\n",
+      "Cost function: 0.24554102877121778\n",
+      "Cost function: 0.24552016553714492\n",
+      "mean 0: 10.47679073233623\n",
+      "sigma 0: 4.260737598822586\n",
+      "mean 1: 3.162121914331882\n",
+      "sigma 1: 0.6912132313825448\n",
+      "mean 2: 1.7669307220546364\n",
+      "sigma 2: 0.2001942501456096\n",
+      "Cost function: 33.624038110459594\n",
+      "Cost function: 6.576615712126629\n",
+      "Cost function: 1.8163913328722827\n",
+      "Cost function: 0.9745349470582501\n",
+      "Cost function: 0.8216274270702817\n",
+      "Cost function: 0.7899048213339446\n",
+      "Cost function: 0.7795479644437096\n",
+      "Cost function: 0.7730069291657166\n",
+      "Cost function: 0.7671955270326364\n",
+      "Cost function: 0.7615704442641105\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "                           Warm up exercise |  10 /  10 | Nice work!\n",
+      "          Computing Cost (for one variable) |  40 /  40 | Nice work!\n",
+      "        Gradient Descent (for one variable) |  50 /  50 | Nice work!\n",
+      "                      Feature Normalization |   0 /   0 | Nice work!\n",
+      "    Computing Cost (for multiple variables) |   0 /   0 | Nice work!\n",
+      "  Gradient Descent (for multiple variables) |   0 /   0 | Nice work!\n",
+      "                           Normal Equations |   0 /   0 | Nice work!\n",
+      "                                  --------------------------------\n",
+      "                                            | 100 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[7] = normalEqn\n",
     "grader.grade()"
@@ -1262,9 +3428,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 126,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Theta computed from the normal equations: [ 89597.90954355    139.21067402  -8738.01911255]\n",
+      "Predicted price of a 1650 sq-ft, 3 br house (using normal equations): $293081\n"
+     ]
+    }
+   ],
    "source": [
     "# Calculate the parameters from the normal equation\n",
     "theta = normalEqn(X, y);\n",
@@ -1275,12 +3450,19 @@
     "# Estimate the price of a 1650 sq-ft, 3 br house\n",
     "# ====================== YOUR CODE HERE ======================\n",
     "\n",
-    "price = 0 # You should change this\n",
+    "price =  [1, 1650, 3] @ theta\n",
     "\n",
     "# ============================================================\n",
     "\n",
     "print('Predicted price of a 1650 sq-ft, 3 br house (using normal equations): ${:.0f}'.format(price))"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -1299,7 +3481,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.4"
+   "version": "3.6.6"
   }
  },
  "nbformat": 4,
diff --git a/Exercise2/exercise2.ipynb b/Exercise2/exercise2.ipynb
index 39983d90..892a1458 100755
--- a/Exercise2/exercise2.ipynb
+++ b/Exercise2/exercise2.ipynb
@@ -19,7 +19,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -89,7 +89,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -125,7 +125,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -151,7 +151,12 @@
     "    fig = pyplot.figure()\n",
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
+    "    pos = y == 1\n",
+    "    neg = y == 0\n",
     "\n",
+    "    # Plot Examples\n",
+    "    pyplot.plot(X[pos, 0], X[pos, 1], 'k*', lw=2, ms=10)\n",
+    "    pyplot.plot(X[neg, 0], X[neg, 1], 'ko', mfc='y', ms=8, mec='k', mew=1)\n",
     "    \n",
     "    # ============================================================"
    ]
@@ -165,9 +170,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 31,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plotData(X, y)\n",
     "# add axes labels\n",
@@ -202,7 +220,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -228,14 +246,12 @@
     "    \"\"\"\n",
     "    # convert input to a numpy array\n",
     "    z = np.array(z)\n",
-    "    \n",
     "    # You need to return the following variables correctly \n",
     "    g = np.zeros(z.shape)\n",
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
-    "\n",
+    "    g = 1 / (1 + np.exp(-z))\n",
     "    \n",
-    "\n",
     "    # =============================================================\n",
     "    return g"
    ]
@@ -249,12 +265,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 33,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "g( [0, 1, -10000000, 10000000000] ) =  [0.5        0.73105858 0.         1.        ]\n"
+     ]
+    }
+   ],
    "source": [
     "# Test the implementation of sigmoid function here\n",
-    "z = 0\n",
+    "z = [0, 1, -10000000, 10000000000]\n",
     "g = sigmoid(z)\n",
     "\n",
     "print('g(', z, ') = ', g)"
@@ -275,9 +299,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 34,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise logistic-regression\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "                           Sigmoid Function |   5 /   5 | Nice work!\n",
+      "                   Logistic Regression Cost |   0 /  30 | \n",
+      "               Logistic Regression Gradient |   0 /  30 | \n",
+      "                                    Predict |   0 /   5 | \n",
+      "       Regularized Logistic Regression Cost |   0 /  15 | \n",
+      "   Regularized Logistic Regression Gradient |   0 /  15 | \n",
+      "                                  --------------------------------\n",
+      "                                            |   5 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "# appends the implemented function in part 1 to the grader object\n",
     "grader[1] = sigmoid\n",
@@ -298,7 +344,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -328,11 +374,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [],
    "source": [
-    "def costFunction(theta, X, y):\n",
+    "def costFunction(theta, X, y, lambda_ = 0):\n",
     "    \"\"\"\n",
     "    Compute cost and gradient for logistic regression. \n",
     "    \n",
@@ -347,7 +393,7 @@
     "        of data points and n is the number of features. We assume the \n",
     "        intercept has already been added to the input.\n",
     "    \n",
-    "    y : arra_like\n",
+    "    y : array_like\n",
     "        Labels for the input. This is a vector of shape (m, ).\n",
     "    \n",
     "    Returns\n",
@@ -371,13 +417,22 @@
     "    # You need to return the following variables correctly \n",
     "    J = 0\n",
     "    grad = np.zeros(theta.shape)\n",
-    "\n",
-    "    # ====================== YOUR CODE HERE ======================\n",
-    "\n",
     "    \n",
+    "    # ====================== YOUR CODE HERE ======================\n",
+    "    ones = np.ones(m)\n",
+    "    hypothesis = sigmoid(np.dot(theta, X.T))\n",
+    "    part_right = np.subtract(ones, y) @ (np.log(np.subtract(ones, hypothesis)))\n",
+    "    part_left = -(y @ np.log(hypothesis))\n",
+    "    error = np.subtract(part_left, part_right)\n",
     "    \n",
+    "    regterm = (lambda_/2) * np.sum(np.dot(theta[1:].T,theta[1:])) #Skip theta0\n",
+    "    grad_regterm = np.zeros(theta.shape[0])\n",
+    "    grad_regterm[1:] = (lambda_/m * theta[1:])\n",
+    "        \n",
+    "    J = (np.sum(error) + regterm) / m\n",
+    "    grads = np.dot(np.divide(X.T, m), np.subtract(sigmoid(np.dot(X,theta)), y)) + grad_regterm\n",
     "    # =============================================================\n",
-    "    return J, grad"
+    "    return J, grads"
    ]
   },
   {
@@ -389,9 +444,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 39,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cost at initial theta (zeros): 0.693\n",
+      "Expected cost (approx): 0.693\n",
+      "\n",
+      "Gradient at initial theta (zeros):\n",
+      "\t[-0.1000, -12.0092, -11.2628]\n",
+      "Expected gradients (approx):\n",
+      "\t[-0.1000, -12.0092, -11.2628]\n",
+      "\n",
+      "Cost at test theta: 0.218\n",
+      "Expected cost (approx): 0.218\n",
+      "\n",
+      "Gradient at test theta:\n",
+      "\t[0.043, 2.566, 2.647]\n",
+      "Expected gradients (approx):\n",
+      "\t[0.043, 2.566, 2.647]\n"
+     ]
+    }
+   ],
    "source": [
     "# Initialize fitting parameters\n",
     "initial_theta = np.zeros(n+1)\n",
@@ -426,9 +503,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 40,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise logistic-regression\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "                           Sigmoid Function |   5 /   5 | Nice work!\n",
+      "                   Logistic Regression Cost |  30 /  30 | Nice work!\n",
+      "               Logistic Regression Gradient |  30 /  30 | Nice work!\n",
+      "                                    Predict |   0 /   5 | \n",
+      "       Regularized Logistic Regression Cost |   0 /  15 | \n",
+      "   Regularized Logistic Regression Gradient |   0 /  15 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  65 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[2] = costFunction\n",
     "grader[3] = costFunction\n",
@@ -459,9 +558,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 41,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cost at theta found by optimize.minimize: 0.203\n",
+      "Expected cost (approx): 0.203\n",
+      "\n",
+      "theta:\n",
+      "\t[-25.161, 0.206, 0.201]\n",
+      "Expected theta (approx):\n",
+      "\t[-25.161, 0.206, 0.201]\n"
+     ]
+    }
+   ],
    "source": [
     "# set options for optimize.minimize\n",
     "options= {'maxiter': 400}\n",
@@ -508,9 +621,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 42,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Plot Boundary\n",
     "utils.plotDecisionBoundary(plotData, theta, X, y)"
@@ -530,7 +656,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -566,8 +692,8 @@
     "    p = np.zeros(m)\n",
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
-    "\n",
-    "    \n",
+    "    probs = sigmoid(X @ theta.transpose())\n",
+    "    p = (probs >= 0.5).astype(int)\n",
     "    \n",
     "    # ============================================================\n",
     "    return p"
@@ -582,9 +708,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 44,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "For a student with scores 45 and 85,we predict an admission probability of 0.776\n",
+      "Expected value: 0.775 +/- 0.002\n",
+      "\n",
+      "Train Accuracy: 89.00 %\n",
+      "Expected accuracy (approx): 89.00 %\n"
+     ]
+    }
+   ],
    "source": [
     "#  Predict probability for a student with score 45 on exam 1 \n",
     "#  and score 85 on exam 2 \n",
@@ -608,9 +746,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 45,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise logistic-regression\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "                           Sigmoid Function |   5 /   5 | Nice work!\n",
+      "                   Logistic Regression Cost |  30 /  30 | Nice work!\n",
+      "               Logistic Regression Gradient |  30 /  30 | Nice work!\n",
+      "                                    Predict |   5 /   5 | Nice work!\n",
+      "       Regularized Logistic Regression Cost |   0 /  15 | \n",
+      "   Regularized Logistic Regression Gradient |   0 /  15 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  70 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[4] = predict\n",
     "grader.grade()"
@@ -630,7 +790,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -654,9 +814,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 47,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plotData(X, y)\n",
     "# Labels and Legend\n",
@@ -686,7 +859,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -718,10 +891,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 53,
    "metadata": {},
    "outputs": [],
    "source": [
+    "\n",
     "def costFunctionReg(theta, X, y, lambda_):\n",
     "    \"\"\"\n",
     "    Compute cost and gradient for logistic regression with regularization.\n",
@@ -767,11 +941,11 @@
     "    grad = np.zeros(theta.shape)\n",
     "\n",
     "    # ===================== YOUR CODE HERE ======================\n",
-    "\n",
     "    \n",
     "    \n",
+    "\n",
     "    # =============================================================\n",
-    "    return J, grad"
+    "    return costFunction(X=X, y=y, theta=theta, lambda_ = lambda_)"
    ]
   },
   {
@@ -783,9 +957,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 54,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cost at initial theta (zeros): 0.693\n",
+      "Expected cost (approx)       : 0.693\n",
+      "\n",
+      "Gradient at initial theta (zeros) - first five values only:\n",
+      "\t[0.0085, 0.0188, 0.0001, 0.0503, 0.0115]\n",
+      "Expected gradients (approx) - first five values only:\n",
+      "\t[0.0085, 0.0188, 0.0001, 0.0503, 0.0115]\n",
+      "\n",
+      "------------------------------\n",
+      "\n",
+      "Cost at test theta    : 3.16\n",
+      "Expected cost (approx): 3.16\n",
+      "\n",
+      "Gradient at initial theta (zeros) - first five values only:\n",
+      "\t[0.3460, 0.1614, 0.1948, 0.2269, 0.0922]\n",
+      "Expected gradients (approx) - first five values only:\n",
+      "\t[0.3460, 0.1614, 0.1948, 0.2269, 0.0922]\n"
+     ]
+    }
+   ],
    "source": [
     "# Initialize fitting parameters\n",
     "initial_theta = np.zeros(X.shape[1])\n",
@@ -832,9 +1030,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 55,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise logistic-regression\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "                           Sigmoid Function |   5 /   5 | Nice work!\n",
+      "                   Logistic Regression Cost |  30 /  30 | Nice work!\n",
+      "               Logistic Regression Gradient |  30 /  30 | Nice work!\n",
+      "                                    Predict |   5 /   5 | Nice work!\n",
+      "       Regularized Logistic Regression Cost |  15 /  15 | Nice work!\n",
+      "   Regularized Logistic Regression Gradient |  15 /  15 | Nice work!\n",
+      "                                  --------------------------------\n",
+      "                                            | 100 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[5] = costFunctionReg\n",
     "grader[6] = costFunctionReg\n",
@@ -892,15 +1112,37 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 56,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Train Accuracy: 87.3 %\n",
+      "Expected accuracy (with lambda = 1): 83.1 % (approx)\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Initialize fitting parameters\n",
     "initial_theta = np.zeros(X.shape[1])\n",
     "\n",
     "# Set regularization parameter lambda to 1 (you should vary this)\n",
-    "lambda_ = 1\n",
+    "lambda_ = 0.0001\n",
     "\n",
     "# set options for optimize.minimize\n",
     "options= {'maxiter': 100}\n",
@@ -939,6 +1181,13 @@
    "source": [
     "*You do not need to submit any solutions for these optional (ungraded) exercises.*"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -957,7 +1206,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.4"
+   "version": "3.7.0"
   }
  },
  "nbformat": 4,
diff --git a/Exercise3/exercise3.ipynb b/Exercise3/exercise3.ipynb
index e37be91f..18049b8e 100755
--- a/Exercise3/exercise3.ipynb
+++ b/Exercise3/exercise3.ipynb
@@ -14,12 +14,12 @@
     "\n",
     "All the information you need for solving this assignment is in this notebook, and all the code you will be implementing will take place within this notebook. The assignment can be promptly submitted to the coursera grader directly from this notebook (code and instructions are included below).\n",
     "\n",
-    "Before we begin with the exercises, we need to import all libraries required for this programming exercise. Throughout the course, we will be using [`numpy`](http://www.numpy.org/) for all arrays and matrix operations, [`matplotlib`](https://matplotlib.org/) for plotting, and [`scipy`](https://docs.scipy.org/doc/scipy/reference/) for scientific and numerical computation functions and tools. You can find instructions on how to install required libraries in the README file in the [github repository](https://github.com/dibgerge/ml-coursera-python-assignments)."
+    "Before we begin with the exercises, we need to import all libraries required for this programming exercise. Throughout the course, we will be using [`numpy`](http://www.numpy.org/) for all arrays a`nd matrix operations, [`matplotlib`](https://matplotlib.org/) for plotting, and [`scipy`](https://docs.scipy.org/doc/scipy/reference/) for scientific and numerical computation functions and tools. You can find instructions on how to install required libraries in the README file in the [github repository](https://github.com/dibgerge/ml-coursera-python-assignments)."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -99,7 +99,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -132,9 +132,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 100 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Randomly select 100 data points to display\n",
     "rand_indices = np.random.choice(m, 100, replace=False)\n",
@@ -158,7 +171,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -267,7 +280,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -348,11 +361,21 @@
     "    grad = np.zeros(theta.shape)\n",
     "    \n",
     "    # ====================== YOUR CODE HERE ======================\n",
-    "\n",
-    "\n",
+    "    ones = np.ones(m)\n",
+    "    hypothesis = utils.sigmoid(np.dot(theta, X.T))\n",
+    "    part_right = np.subtract(ones, y) @ (np.log(np.subtract(ones, hypothesis)))\n",
+    "    part_left = -(y @ np.log(hypothesis))\n",
+    "    error = np.subtract(part_left, part_right)\n",
+    "    \n",
+    "    regterm = (lambda_/2) * np.sum(np.dot(theta[1:].T,theta[1:])) #Skip theta0\n",
+    "    grad_regterm = np.zeros(theta.shape[0])\n",
+    "    grad_regterm[1:] = (lambda_/m * theta[1:])\n",
     "        \n",
+    "    J = (np.sum(error) + regterm) / m\n",
+    "    grads = np.dot(np.divide(X.T, m), np.subtract(utils.sigmoid(np.dot(X,theta)), y)) + grad_regterm\n",
+    "     \n",
     "    # =============================================================\n",
-    "    return J, grad"
+    "    return J, grads"
    ]
   },
   {
@@ -389,9 +412,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cost         : 2.534819\n",
+      "Expected cost: 2.534819\n",
+      "-----------------------\n",
+      "Gradients:\n",
+      " [0.146561, -0.548558, 0.724722, 1.398003]\n",
+      "Expected gradients:\n",
+      " [0.146561, -0.548558, 0.724722, 1.398003]\n"
+     ]
+    }
+   ],
    "source": [
     "J, grad = lrCostFunction(theta_t, X_t, y_t, lambda_t)\n",
     "\n",
@@ -417,9 +454,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise multi-class-classification-and-neural-networks\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "            Regularized Logistic Regression |  30 /  30 | Nice work!\n",
+      "             One-vs-All Classifier Training |   0 /  20 | \n",
+      "           One-vs-All Classifier Prediction |   0 /  20 | \n",
+      "         Neural Network Prediction Function |   0 /  30 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  30 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "# appends the implemented function in part 1 to the grader object\n",
     "grader[1] = lrCostFunction\n",
@@ -448,7 +505,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -526,9 +583,16 @@
     "    X = np.concatenate([np.ones((m, 1)), X], axis=1)\n",
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
-    "   \n",
-    "\n",
-    "\n",
+    "    for k in range(num_labels):\n",
+    "        initial_theta = np.zeros(n+1)\n",
+    "        options = {'maxiter': 25}\n",
+    "        res = optimize.minimize(lrCostFunction, \n",
+    "                                initial_theta, \n",
+    "                                (X, (y == k), lambda_), \n",
+    "                                jac=True, \n",
+    "                                method='TNC',\n",
+    "                                options=options)\n",
+    "        all_theta[k, ] = res.x\n",
     "    # ============================================================\n",
     "    return all_theta"
    ]
@@ -542,7 +606,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -559,9 +623,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise multi-class-classification-and-neural-networks\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "            Regularized Logistic Regression |  30 /  30 | Nice work!\n",
+      "             One-vs-All Classifier Training |  20 /  20 | Nice work!\n",
+      "           One-vs-All Classifier Prediction |   0 /  20 | \n",
+      "         Neural Network Prediction Function |   0 /  30 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  50 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[2] = oneVsAll\n",
     "grader.grade()"
@@ -580,7 +664,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -634,11 +718,11 @@
     "    X = np.concatenate([np.ones((m, 1)), X], axis=1)\n",
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
+    "    probs = utils.sigmoid(X @ all_theta.transpose())\n",
+    "    probs = np.argmax(probs, axis=1)\n",
     "\n",
-    "\n",
-    "    \n",
     "    # ============================================================\n",
-    "    return p"
+    "    return probs"
    ]
   },
   {
@@ -650,9 +734,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 27,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Training Set Accuracy: 92.30%\n"
+     ]
+    }
+   ],
    "source": [
     "pred = predictOneVsAll(all_theta, X)\n",
     "print('Training Set Accuracy: {:.2f}%'.format(np.mean(pred == y) * 100))"
@@ -667,9 +759,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 28,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise multi-class-classification-and-neural-networks\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "            Regularized Logistic Regression |  30 /  30 | Nice work!\n",
+      "             One-vs-All Classifier Training |  20 /  20 | Nice work!\n",
+      "           One-vs-All Classifier Prediction |  20 /  20 | Nice work!\n",
+      "         Neural Network Prediction Function |   0 /  30 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  70 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[3] = predictOneVsAll\n",
     "grader.grade()"
@@ -690,9 +802,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 29,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 100 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "#  training data stored in arrays X, y\n",
     "data = loadmat(os.path.join('Data', 'ex3data1.mat'))\n",
@@ -735,7 +860,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -774,7 +899,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 58,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -833,8 +958,18 @@
     "    p = np.zeros(X.shape[0])\n",
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
+    "    # Add a row of ones to our training data (bias)\n",
+    "    X = np.concatenate([np.ones((m, 1)), X], axis=1)\n",
+    "    \n",
+    "    Z2 = X @ Theta1.T\n",
+    "    A2 = utils.sigmoid(Z2)\n",
+    "    A2 = np.concatenate([np.ones((A2.shape[0], 1)), A2], axis=1)\n",
+    "    \n",
+    "    Z3 = A2 @ Theta2.T\n",
+    "    A3 = utils.sigmoid(Z3)\n",
     "\n",
-    "\n",
+    "    # probs = utils.sigmoid(X @ all_theta.transpose())\n",
+    "    p = np.argmax(A3, axis=1)\n",
     "\n",
     "    # =============================================================\n",
     "    return p"
@@ -849,9 +984,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 59,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Training Set Accuracy: 97.5%\n"
+     ]
+    }
+   ],
    "source": [
     "pred = predict(Theta1, Theta2, X)\n",
     "print('Training Set Accuracy: {:.1f}%'.format(np.mean(pred == y) * 100))"
@@ -868,9 +1011,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 60,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Neural Network Prediction: 4\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 288x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "if indices.size > 0:\n",
     "    i, indices = indices[0], indices[1:]\n",
@@ -892,7 +1055,18 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise multi-class-classification-and-neural-networks\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n"
+     ]
+    }
+   ],
    "source": [
     "grader[4] = predict\n",
     "grader.grade()"
@@ -915,7 +1089,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.4"
+   "version": "3.7.0"
   }
  },
  "nbformat": 4,
diff --git a/Exercise4/exercise4.ipynb b/Exercise4/exercise4.ipynb
index d8ebee0c..4f55dc8e 100755
--- a/Exercise4/exercise4.ipynb
+++ b/Exercise4/exercise4.ipynb
@@ -18,7 +18,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -87,7 +87,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 109,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -128,9 +128,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 110,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 100 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Randomly select 100 data points to display\n",
     "rand_indices = np.random.choice(m, 100, replace=False)\n",
@@ -157,7 +170,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 111,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -215,7 +228,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 112,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -316,14 +329,41 @@
     "    Theta2_grad = np.zeros(Theta2.shape)\n",
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
+    "    # Forward propagation\n",
+    "    # Add a row of ones to our training data (bias)\n",
+    "    X = np.concatenate([np.ones((m, 1)), X], axis=1)\n",
+    "    \n",
+    "    Z2 = X @ Theta1.T\n",
+    "    A2 = utils.sigmoid(Z2)\n",
+    "    A2 = np.concatenate([np.ones((A2.shape[0], 1)), A2], axis=1)\n",
+    "    \n",
+    "    Z3 = A2 @ Theta2.T\n",
+    "    A3 = utils.sigmoid(Z3)\n",
+    "    # p = np.argmax(A3, axis=1)\n",
+    "    \n",
+    "    # convert y to one hot encoding scheme\n",
+    "    y_hot = np.max(y) + 1\n",
+    "    y_hot = np.eye(y_hot)[y]\n",
+    "    \n",
+    "    # Cost function\n",
+    "    regterm = (lambda_ / (2*m)) * (np.sum(np.square(Theta1[:,1:])) + np.sum(np.square(Theta2[:,1:])))\n",
+    "    J = -1*(1/m) * np.sum((np.log(A3)*(y_hot) + np.log(1-A3) * (1-y_hot))) + regterm\n",
     "\n",
+    "    # Backpropagation\n",
+    "    error3 = A3 - y_hot\n",
+    "    error2 = np.dot(Theta2[:,1:].T, error3.T) * sigmoidGradient(Z2).T\n",
+    "    \n",
+    "    delta1 = np.dot(error2, X)\n",
+    "    delta2 = np.dot(error3.T, A2)\n",
     "    \n",
+    "    Theta1_grad[:,1:] = (delta1[:,1:]/m) + ((lambda_/m) * Theta1[:,1:])\n",
+    "    Theta2_grad[:,1:] = (delta2[:,1:]/m) + ((lambda_/m) / Theta2[:,1:])\n",
     "    \n",
     "    # ================================================================\n",
     "    # Unroll gradients\n",
     "    # grad = np.concatenate([Theta1_grad.ravel(order=order), Theta2_grad.ravel(order=order)])\n",
     "    grad = np.concatenate([Theta1_grad.ravel(), Theta2_grad.ravel()])\n",
-    "\n",
+    "    \n",
     "    return J, grad"
    ]
   },
@@ -351,9 +391,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 113,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cost at parameters (loaded from ex4weights): 0.287629 \n",
+      "The cost should be about                   : 0.287629.\n"
+     ]
+    }
+   ],
    "source": [
     "lambda_ = 0\n",
     "J, _ = nnCostFunction(nn_params, input_layer_size, hidden_layer_size,\n",
@@ -371,9 +420,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 77,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise neural-network-learning\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "(4, 3)\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "              Feedforward and Cost Function |  30 /  30 | Nice work!\n",
+      "                  Regularized Cost Function |   0 /  15 | \n",
+      "                           Sigmoid Gradient |   0 /   5 | \n",
+      "  Neural Network Gradient (Backpropagation) |   0 /  40 | \n",
+      "                       Regularized Gradient |   0 /  10 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  30 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader = utils.Grader()\n",
     "grader[1] = nnCostFunction\n",
@@ -407,9 +478,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 78,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(25, 401)\n",
+      "Cost at parameters (loaded from ex4weights): 0.383770\n",
+      "This value should be about                 : 0.383770.\n"
+     ]
+    }
+   ],
    "source": [
     "# Weight regularization parameter (we set this to 1 here).\n",
     "lambda_ = 1\n",
@@ -429,9 +510,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 79,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise neural-network-learning\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "(4, 3)\n",
+      "(4, 3)\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "              Feedforward and Cost Function |  30 /  30 | Nice work!\n",
+      "                  Regularized Cost Function |  15 /  15 | Nice work!\n",
+      "                           Sigmoid Gradient |   0 /   5 | \n",
+      "  Neural Network Gradient (Backpropagation) |   0 /  40 | \n",
+      "                       Regularized Gradient |   0 /  10 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  45 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[2] = nnCostFunction\n",
     "grader.grade()"
@@ -470,7 +574,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 103,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -506,7 +610,7 @@
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
     "\n",
-    "\n",
+    "    g = utils.sigmoid(z) * (1 - utils.sigmoid(z))\n",
     "\n",
     "    # =============================================================\n",
     "    return g"
@@ -521,9 +625,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 104,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Sigmoid gradient evaluated at [-1 -0.5 0 0.5 1]:\n",
+      "  \n",
+      "[0.19661193 0.23500371 0.25       0.23500371 0.19661193]\n"
+     ]
+    }
+   ],
    "source": [
     "z = np.array([-1, -0.5, 0, 0.5, 1])\n",
     "g = sigmoidGradient(z)\n",
@@ -540,9 +654,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 105,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise neural-network-learning\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "(4, 3)\n",
+      "(4, 3)\n",
+      "(4, 3)\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "              Feedforward and Cost Function |  30 /  30 | Nice work!\n",
+      "                  Regularized Cost Function |  15 /  15 | Nice work!\n",
+      "                           Sigmoid Gradient |   5 /   5 | Nice work!\n",
+      "  Neural Network Gradient (Backpropagation) |  40 /  40 | Nice work!\n",
+      "                       Regularized Gradient |   0 /  10 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  90 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[3] = sigmoidGradient\n",
     "grader.grade()"
@@ -571,7 +709,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 106,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -610,6 +748,7 @@
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
     "\n",
+    "    W = np.random.rand(L_out, 1 + L_in) * 2 * epsilon_init - epsilon_init\n",
     "\n",
     "\n",
     "    # ============================================================\n",
@@ -627,9 +766,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 107,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Initializing Neural Network Parameters ...\n",
+      "[-0.06178768 -0.02944607  0.03313469 ... -0.08068901 -0.0248455\n",
+      " -0.1050666 ]\n"
+     ]
+    }
+   ],
    "source": [
     "print('Initializing Neural Network Parameters ...')\n",
     "\n",
@@ -637,7 +786,8 @@
     "initial_Theta2 = randInitializeWeights(hidden_layer_size, num_labels)\n",
     "\n",
     "# Unroll parameters\n",
-    "initial_nn_params = np.concatenate([initial_Theta1.ravel(), initial_Theta2.ravel()], axis=0)"
+    "initial_nn_params = np.concatenate([initial_Theta1.ravel(), initial_Theta2.ravel()], axis=0)\n",
+    "print(initial_nn_params)"
    ]
   },
   {
@@ -716,9 +866,60 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 114,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[-9.27825235e-03  0.00000000e+00]\n",
+      " [-3.04978709e-06 -3.04978914e-06]\n",
+      " [-1.75060084e-04 -1.75060082e-04]\n",
+      " [-9.62660640e-05 -9.62660620e-05]\n",
+      " [ 8.89911959e-03  0.00000000e+00]\n",
+      " [ 1.42869450e-05  1.42869443e-05]\n",
+      " [ 2.33146358e-04  2.33146357e-04]\n",
+      " [ 1.17982666e-04  1.17982666e-04]\n",
+      " [-8.36010761e-03  0.00000000e+00]\n",
+      " [-2.59383093e-05 -2.59383100e-05]\n",
+      " [-2.87468729e-04 -2.87468729e-04]\n",
+      " [-1.37149709e-04 -1.37149706e-04]\n",
+      " [ 7.62813550e-03  0.00000000e+00]\n",
+      " [ 3.69883257e-05  3.69883234e-05]\n",
+      " [ 3.35320351e-04  3.35320347e-04]\n",
+      " [ 1.53247082e-04  1.53247082e-04]\n",
+      " [-6.74798369e-03  0.00000000e+00]\n",
+      " [-4.68759742e-05 -4.68759769e-05]\n",
+      " [-3.76215583e-04 -3.76215587e-04]\n",
+      " [-1.66560294e-04 -1.66560294e-04]\n",
+      " [ 3.14544970e-01  0.00000000e+00]\n",
+      " [ 1.64090819e-01  1.64090819e-01]\n",
+      " [ 1.64567932e-01  1.64567932e-01]\n",
+      " [ 1.58339334e-01  1.58339334e-01]\n",
+      " [ 1.51127527e-01  1.51127527e-01]\n",
+      " [ 1.49568335e-01  1.49568335e-01]\n",
+      " [ 1.11056588e-01  0.00000000e+00]\n",
+      " [ 5.75736494e-02  5.75736493e-02]\n",
+      " [ 5.77867378e-02  5.77867378e-02]\n",
+      " [ 5.59235296e-02  5.59235296e-02]\n",
+      " [ 5.36967009e-02  5.36967009e-02]\n",
+      " [ 5.31542052e-02  5.31542052e-02]\n",
+      " [ 9.74006970e-02  0.00000000e+00]\n",
+      " [ 5.04575855e-02  5.04575855e-02]\n",
+      " [ 5.07530173e-02  5.07530173e-02]\n",
+      " [ 4.91620841e-02  4.91620841e-02]\n",
+      " [ 4.71456249e-02  4.71456249e-02]\n",
+      " [ 4.65597186e-02  4.65597186e-02]]\n",
+      "The above two columns you get should be very similar.\n",
+      "(Left-Your Numerical Gradient, Right-Analytical Gradient)\n",
+      "\n",
+      "If your backpropagation implementation is correct, then \n",
+      "the relative difference will be small (less than 1e-9). \n",
+      "Relative Difference: 0.407869\n"
+     ]
+    }
+   ],
    "source": [
     "utils.checkNNGradients(nnCostFunction)"
    ]
@@ -732,9 +933,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 87,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise neural-network-learning\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "(4, 3)\n",
+      "(4, 3)\n",
+      "(4, 3)\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "              Feedforward and Cost Function |  30 /  30 | Nice work!\n",
+      "                  Regularized Cost Function |  15 /  15 | Nice work!\n",
+      "                           Sigmoid Gradient |   0 /   5 | \n",
+      "  Neural Network Gradient (Backpropagation) |  40 /  40 | Nice work!\n",
+      "                       Regularized Gradient |   0 /  10 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  85 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[4] = nnCostFunction\n",
     "grader.grade()"
@@ -774,9 +999,142 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 89,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "(5, 4)\n",
+      "[[-9.27825235e-03  0.00000000e+00]\n",
+      " [-1.67679797e-02 -1.67679797e-02]\n",
+      " [-6.01744725e-02 -6.01744725e-02]\n",
+      " [-1.73704651e-02 -1.73704651e-02]\n",
+      " [ 8.89911959e-03  0.00000000e+00]\n",
+      " [ 3.94334829e-02  3.94334829e-02]\n",
+      " [-3.19612287e-02 -3.19612287e-02]\n",
+      " [-5.75658668e-02 -5.75658668e-02]\n",
+      " [-8.36010761e-03  0.00000000e+00]\n",
+      " [ 5.93355565e-02  5.93355565e-02]\n",
+      " [ 2.49225535e-02  2.49225535e-02]\n",
+      " [-4.51963845e-02 -4.51963845e-02]\n",
+      " [ 7.62813550e-03  0.00000000e+00]\n",
+      " [ 2.47640974e-02  2.47640974e-02]\n",
+      " [ 5.97717617e-02  5.97717617e-02]\n",
+      " [ 9.14587966e-03  9.14587966e-03]\n",
+      " [-6.74798369e-03  0.00000000e+00]\n",
+      " [-3.26881426e-02 -3.26881426e-02]\n",
+      " [ 3.86410548e-02  3.86410548e-02]\n",
+      " [ 5.46101547e-02  5.46101547e-02]\n",
+      " [ 3.14544970e-01  0.00000000e+00]\n",
+      " [ 1.18682669e-01 -7.76400143e+00]\n",
+      " [ 2.03987128e-01  9.29717431e+00]\n",
+      " [ 1.25698067e-01 -1.08706444e+01]\n",
+      " [ 1.76337550e-01  1.44311625e+01]\n",
+      " [ 1.32294136e-01 -2.06907612e+01]\n",
+      " [ 1.11056588e-01  0.00000000e+00]\n",
+      " [ 3.81928689e-05 -6.19943763e+00]\n",
+      " [ 1.17148233e-01  6.12232405e+00]\n",
+      " [-4.07588279e-03 -5.94413523e+00]\n",
+      " [ 1.13133142e-01  6.11058692e+00]\n",
+      " [-4.52964427e-03 -6.18776077e+00]\n",
+      " [ 9.74006970e-02  0.00000000e+00]\n",
+      " [ 3.36926556e-02 -2.14229397e+01]\n",
+      " [ 7.54801264e-02  1.46096729e+01]\n",
+      " [ 1.69677090e-02 -1.11329155e+01]\n",
+      " [ 8.61628953e-02  9.27382899e+00]\n",
+      " [ 1.50048382e-03 -7.94292349e+00]]\n",
+      "The above two columns you get should be very similar.\n",
+      "(Left-Your Numerical Gradient, Right-Analytical Gradient)\n",
+      "\n",
+      "If your backpropagation implementation is correct, then \n",
+      "the relative difference will be small (less than 1e-9). \n",
+      "Relative Difference: 0.998151\n",
+      "(25, 401)\n",
+      "\n",
+      "\n",
+      "Cost at (fixed) debugging parameters (w/ lambda = 3.000000): 0.576051 \n",
+      "(for lambda = 3, this value should be about 0.576051)\n"
+     ]
+    }
+   ],
    "source": [
     "#  Check gradients by running checkNNGradients\n",
     "lambda_ = 3\n",
@@ -792,9 +1150,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 26,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise neural-network-learning\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "              Feedforward and Cost Function |  30 /  30 | Nice work!\n",
+      "                  Regularized Cost Function |  15 /  15 | Nice work!\n",
+      "                           Sigmoid Gradient |   5 /   5 | Nice work!\n",
+      "  Neural Network Gradient (Backpropagation) |  40 /  40 | Nice work!\n",
+      "                       Regularized Gradient |   0 /  10 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  90 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[5] = nnCostFunction\n",
     "grader.grade()"
@@ -812,7 +1191,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 115,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -858,9 +1237,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 116,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Training Set Accuracy: 84.660000\n"
+     ]
+    }
+   ],
    "source": [
     "pred = utils.predict(Theta1, Theta2, X)\n",
     "print('Training Set Accuracy: %f' % (np.mean(pred == y) * 100))"
@@ -883,9 +1270,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 117,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 25 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "utils.displayData(Theta1[:, 1:])"
    ]
@@ -916,7 +1316,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.4"
+   "version": "3.7.0"
   }
  },
  "nbformat": 4,
diff --git a/Exercise5/exercise5.ipynb b/Exercise5/exercise5.ipynb
index 66c4500e..77083533 100755
--- a/Exercise5/exercise5.ipynb
+++ b/Exercise5/exercise5.ipynb
@@ -18,10 +18,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 1,
+   "metadata": {},
    "outputs": [],
    "source": [
     "# used for manipulating directory paths\n",
@@ -99,9 +97,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Load from ex5data1.mat, where all variables will be store in a dictionary\n",
     "data = loadmat(os.path.join('Data', 'ex5data1.mat'))\n",
@@ -140,10 +151,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 3,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def linearRegCostFunction(X, y, theta, lambda_=0.0):\n",
@@ -192,11 +201,9 @@
     "    grad = np.zeros(theta.shape)\n",
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
-    "\n",
-    "\n",
-    "\n",
-    "    # ============================================================\n",
-    "    return J, grad"
+    "    J = (1/(2*m)) * np.sum(np.square((X @ theta.T) - y)) + (lambda_/(2*m)) * np.sum(np.square(theta[1:]))\n",
+    "    grad = (1/m)* (X.T.dot(X @ theta.T -y)) + (lambda_/m) * np.array([0 if i == 0 else theta[i] for i in range(len(theta))])\n",
+    "    return J, grad.flatten()"
    ]
   },
   {
@@ -208,9 +215,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cost at theta = [1, 1]:\t   303.993192 \n",
+      "This value should be about 303.993192)\n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "theta = np.array([1, 1])\n",
     "J, _ = linearRegCostFunction(np.concatenate([np.ones((m, 1)), X], axis=1), y, theta, 1)\n",
@@ -232,9 +249,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise regularized-linear-regression-and-bias-variance\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "Regularized Linear Regression Cost Function |  25 /  25 | Nice work!\n",
+      "     Regularized Linear Regression Gradient |   0 /  25 | \n",
+      "                             Learning Curve |   0 /  20 | \n",
+      "                 Polynomial Feature Mapping |   0 /  10 | \n",
+      "                           Validation Curve |   0 /  20 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  25 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[1] = linearRegCostFunction\n",
     "grader.grade()"
@@ -264,9 +302,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Gradient at theta = [1, 1]:  [-15.303016, 598.250744] \n",
+      " (this value should be about [-15.303016, 598.250744])\n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "theta = np.array([1, 1])\n",
     "J, grad = linearRegCostFunction(np.concatenate([np.ones((m, 1)), X], axis=1), y, theta, 1)\n",
@@ -284,9 +332,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise regularized-linear-regression-and-bias-variance\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "Regularized Linear Regression Cost Function |  25 /  25 | Nice work!\n",
+      "     Regularized Linear Regression Gradient |  25 /  25 | Nice work!\n",
+      "                             Learning Curve |   0 /  20 | \n",
+      "                 Polynomial Feature Mapping |   0 /  10 | \n",
+      "                           Validation Curve |   0 /  20 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  50 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[2] = linearRegCostFunction\n",
     "grader.grade()"
@@ -312,9 +381,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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r1qxj2JXT+HL1uoRtz084UI3AWZaq19BNwE1mdou7n9naA1vw1X8KUN9kXqKHgdOAa8N/H2rtsUWkbXJ3bnp6KTc89UrCtsVXHKpuoDkSpdfQmWa2O7BPWDTD3RMn9U40EjgVWGRmL4ZllxAkgPvNrIxgDiNNVyHSzq1as46/zXuHBxe8S6cO30563KtbZ2b8en/dAeRYlIVpziWoq2+o2rnbzCa7+/9L9Tp3fxaaXUXuoFZFKSJt0usffsGB1/97g7IxI/tz4OCtOe0H/ei0WZSZ8CXToqThXwAj3P1LADObCMwCUiYCESlcb674kv2ueyah/OafDeXw0m3VCJxnoiQCI1iiskHDcpUiIhtY+sEXjJ7076TbXvvDEXRQAshLURLB7cBsM3swfH4sQSOwiAgAH37+DXte/VTSbUuvPpzNOqgKKJ9FaSyeZGbPAKMI7gROd/cFmQ5MRPLfax9+wUHXJ94BxAxevVp3AG1FpKZ6d58PzM9wLCLSRjz76kecMmV2Qvl+A3vz59P3JOrAUckP6rMlIpE9v/QjfladmAB+NqIvVx9bqgTQRikRiEiLZr76IadOqUm67Y1rjlACaOOijCOY6O4XtVQmIu1Pc72AunSM8fKVh+cgIsmEKHcEB5M4TfThScpEpJ24f87b/PrviRMI9OrWmbmXjc5BRJJJqaahPhM4CxhgZo3fEd2B5zIdmIhk3//NfZsL/5aYAC47sphf7NPiPJPSRqW6I7gHeBy4hmAVsQafR52CWkTahml1yym/c25C+Ul79eWa43bNQUSSTalmH/0U+NTMmlYBdTOzbu7+VmZDE5FMe2zR+5x1d2LP8O907ciCyw/JQUSSC1HaCKYSrD9gQBegP7AEGJLBuEQkg2a/voKfTn4hoXzfgb25c8xeOYhIcinKyOIN7gvNbCgwLmMRiUjG/PKvC3jkpfcSyo/cdTtuPnloDiKSfNDqcQTuPt/M9sxEMCKSGVc8Usvtzy1LKL/1lGEcVrptRs7p7tTV1bFy5UqKioooKSnReIM8FWUcQUWjpzFgKPBhxiISkbS59MFF3D07sTnvlL37ctWxmWkEdnemTJnCjZMmUVtfv758SHEx4ysqKCsrU0LIM1HuCLo3+nktQZvB3zMTjoikw9SF73P2PYmNwOX79OfSI0sydl53Z9y4cVRVVTEsFqOSYHHz14HJS5ZQXl5OTU0NlZWVSgZ5JEobwRUAZtY9eOpfZDwqEdkoN09fynVPLEkov+rYUk7Ze6eMn3/KlClUVVVxMXB1PL7BwiXl8XiwVm1VFSNGjKCsrCzj8Ug05u6pdzArBe4CisKij4DT3H1xhmNbb/jw4T53bmIfZxEJDL/qKT764puE8ht/+j2O3WOHrMTg7uw6ZAhdlixhTpMksH4fYHgsxurBg1m4eLHuCjLMzOa5+/CW9otSNTQZqHD36eGB9w/LfrBJEYrIJvvRn55jwVufJJQ/eNYP2KPvd7IaS11dHbX19VTS/BKGBoyNxzmjro76+npKSjJXTSXRRUkEWzQkAQB3f8bMtshgTCLSgkNvmMGS5Z8nlI8fvQvjRw/MQUSwcmUw4UBLE1E0bF+xYkVG45HooiSC183sNwTVQwCnAG9kLiQRac6UZ9/gykfrEsonnbA7xw3tk4OIvlVUFNQev97Cfg3be/bsmdF4JLooiWAMcAXwQPh8BnB6xiISkQRH3jST2vc+Syiv+vlwDi7ZJgcRJSopKWFIcXHQOyhFG8HkWIzSwYMpLi7OdojSjCi9hj4Gzs1CLCLSRL8JU5OWP3nevgzcpnvSbbliZoyvqKC8vJxLgavZsK3AgUuA+fE41RUVaijOI1qhTCTPuDsllz/B12vWJWx7Yvy+DNo2vxJAY2VlZdTU1HBNVRVPxGKMjce/HUcQizE/Hqe8vJwxY8bkOlRpRIlAJE+4O/0vfizptnyqAkrFzKisrGTEiBHccP31nNF4ZPGgQVSffz5jxozR3UCeaXEcQT7QOAJpz+JxZ8AlyRPAA2f9gKFZ7gaaLu5OfX09K1asoGfPnhQXFysBZFnaxhGY2U1Jij8F5rr7QxsTnIjAmnVxdrn08aTbbv+vPTlg8NZZjii9zEzjBNqIKFVDXYDBwP+Fz38M1AJlZnaAu4/PVHAi7VGqBJDvbQDSPkVJBDsDB7r7WgAzuwV4kmBR+0UZjE2kXfl69TqKL/9n0m1Tzx3FkO23ynJEIoEoiWAHYAuC6iDCn7d393Vmlji5iYhsYNWadQz+TfIE8K/z92NA725ZjkhkQ1ESwX8DL5rZMwTdgvcF/hBOM/FUBmMTadM+W7WG3X73ZNJtz084kO17bJ7liESSizKgbIqZPQbsRZAILnH3hrXuLsxkcCJt0YovvmHYVcm/I/37wv3Zqaem6pL8EnUcQYxgVbLNgJ3NbGd3n5G5sETano+/XM0eV05Lum3eZaPp2a1zliMSiSZK99GJwE8JegrFw2InmHNIpOC9teIr9r1uetJtsy4+kO22UhWQ5LcodwTHAoPcXQ3DIo3859NV7H3N00m3Lb7iULp11sB9aRsiTUMNdASUCESAuvc+44ibZibd9vKVh9GlY4csRySyaaIkgq8Ieg09TaNk4O6akVQKyrKPvmT//3km6bb63x/G5p2UAKRtipIIHg4fIgXpnY+/YtTE5G0Ar1x1OJ02i2U5IpH0itJ99I6NObCZ3QYcBXzg7qVhWRFwH9APWAacEK53IJJ35i5byfG3zkq6TQlA2pNmE4GZ3e/uJ5jZIoJeQhtw991aOPafgf8F7mxUNgF42t2vNbMJ4fOLWh21SAa9+PYnHHvzc0m3vfaHI+gQ0wya0r6kuiP4VfjvURtzYHefYWb9mhQfA+wf/nwH8AxKBJIn7pq1jN88VJt02+t/OIKYEoC0U80mAnd/P/zxIGCmu7+ahvNt03Bcd3/fzJqdZ9fMxgJjAfr27ZuGU4sk99zSjzi5enbSbW9cc4Tm0Jd2L0pjcT/gFDPbCZgHzCRIDC9mMjB3nwxMhmBhmkyeSwpTqjsAJQApJFEaiy8HMLPNgXKC+YVuBDamr9xyM9suvBvYDvhgI44hskmmLnyfs++Zn3TbsmuPzHI0IrkXZYqJy4CRQDdgAXABwV3BxngYOA24NvxXK5xJ1vy15i0ufiBxCY09+vbgwbNG5iAikfwQpWroOGAtMBX4N/CCu69q6UVm9leChuFeZvYO8FuCBHC/mZUBbwE/2ci4RSI76+55PLboP0m36Q5AJFrV0FAz6w6MIliVrMrMlrv7qBZed1Izmw5qfZgirXfnrGVcnqQNYNcdtuKRX6Z8+4oUlChVQ6XAPsB+wHDgbTa+akgk48bdNZcnapcn3VaodwDuTl1dHStXrqSoqIiSkhI1hst6UaqGJhJMOX0TMMfd12Q2JJGN88enXuWGp15JKD9gUG9uP32vHESUe+7OlClTuHHSJGrr69eXDykuZnxFBWVlZUoIEqlq6Egz6wQMBAaZ2RIlA8knY++cy5N1iXcApTtsyaO/3CcHEeUHd2fcuHFUVVUxLBajEhhAMJ3w5CVLKC8vp6amhsrKSiWDAhelamg/gmkilhEsVbmjmZ2mFcok186+Zz5TF76fUD66eBuqTxueg4jyy5QpU6iqquJi4Op4nMYf9eXxOJcA11ZVMWLECMrKynIUpeQDc089VsvM5gE/c/cl4fOBwF/dfVgW4gOCAWVz587N1ukkz1364CLunv1WQvmJe+7ItT9uaQqswuDu7DpkCF2WLGFOkySwfh9geCzG6sGDWbh4se4K2iEzm+fuLX4ritJG0LEhCQC4+ytm1nGTohPZCEOvnMbKL1cnlG/ZZTMW/u7QHESUv+rq6qitr6cSkiYBwvKx8Thn1NVRX19PSUlJFiOUfBIlEcw1synAXeHzkwmmmhDJiv2vm86yFV8llI8fvQvjRw/MQUT5b+XKlUDQJpBKw/YVK1ZkNB7Jb1ESwZnA2cC5BF8iZgB/ymRQIgD9JkxNWn5IyTZM/rnaAFIpKioCgobhVBq29+zZM6PxSH5rsY0gH6iNoLD0v3gqyd6Wv/thCf81sn/2A2qD1EYgkIY2guYWpGkQYWEakVYZcPFU4knecafuvRNXHlua/YDaMDNjfEUF5eXlXApczYZtBQ5cAsyPx6muqFASKHCpqoZ+AnydrUCkcDVXBaQEsGnKysqoqanhmqoqnojFGBuPfzuOIBZjfjxOeXk5Y8aMyXWokmOpEsE94TxDd7n7qVmLSApGcwngymNLOXXvnbIcTftjZlRWVjJixAhuuP56zmg8snjQIKrPP58xY8bobkCabyMws8XAdcDlBGsQbMDdH8hsaN9SG0H74e70v/ixpNsuO7KYX+zTUj8X2RjuTn19PStWrKBnz54UFxcrARSAdIwjOIOgq2gP4IdNtjmQtUQgbV+qBFB56jAOHbJtliMqLGamcQLSrFRrFj8LPGtmc919ShZjknYkHncGXJI8AagXkEh+iDLpnJKAtFqqBPCXshGM2qVXliMSkeZEGVAmEtnqtXEGXvZ40m2P/nIUpTtsleWIRKQlKROBBa1Jfdz97SzFI23UN2vXMeiyfybd9tDZI9l9xx5ZjkhEokqZCNzdzewfQNZmGs0lreLUeqvWrGPwb5IngMd/tQ/F222Z5YjaB70XJZtiEfZ5wcz2zHgkOeTuVFdXs+uQIZSWlrLvvvtSWlrKrkOGUF1dTVuYhiPbvvhmLf0mTE2aBP5avjfLrj1SSWAj6L0ouRBlPYI6YBDBwjRfEoxU92xOMZHJcQRNV3FqOvpyXjj6Uqs4BT79eg27X/Fk0m0zLjyAvj27Zjmi9kPvRUm3dK5HcHga4slbWsUpmrdXfsU+/z096bbpF+xP/15bZDmi9kfvRcmVSLOPmtkoYBd3v93MegPd3P2NjEcXytQdgWZobNkHn61irz88nXTb/N8cTNEWnbIcUfuk96JkQtruCMzst8Bwguqh24GOwF+AkZsaZCZFaWzTKk7NW/bRl+z/P88k3Tb3stH06tY5uwG1c3ovSi5FqRr6EbAHMB/A3d8zs+4ZjWoTuDtTpkzhxkmTqG08yVZxMeMrKigrK1ufEPJ5Fadc9Rp55+OvGDUxeRVQzSUHsfWWXTIeQyHK5/eitH9REsHqsBupA5hZ3lYGN21sq4RvG9uWLKG8vJyampr1jW35uIpTaxJZOi394HNGT5qRdFvtFYeyRWeNPcykfHwvSuGI0mvoAmAX4GDgGmAM8Fd3vynz4QWithFUV1dTXl4eNLaRfCGOa8P9ysrK8q5eNhe9Rv718nLG/Dn5ta3//WFs3qlDWs6zsbJxZ5QPffbz7b0o7UPUNgLcvcUHQRK4Dvgf4OAor0nnY9iwYd6SeDzuQ4qLfVgs5nFwT/KIgw+Nxby0pMTj8bi7u1dVVTngF4fbm+4/Ifj78+rq6hZj2FTZjGXBWx/7Thc9mvSxeu26NPw2myYej3tVVZUPKS52wt8b8CHFxV5VVbX+/y/fz9Ea+fRelPYBmOtRPuNb3AEmRinL5CNKIli8eLEDXtlMEmh43Br+MdXW1rp78GFQXl7uhEniVvAnw/2GxmIOeHl5ecY/FDY2kbXWv+qX53UCcN/w/2RYLOaV4NPC/9thafo/ycY5NiWmXL4Xpf1IZyKYn6RsYZSDp+sRJRHMmDHDCf+YUyWCJ8NEMGPGjPWvjcfjXl1dnfSbYXV1dVb+8DY2kUU1/82VzSaAtevy64MlG9+M8/Xbdz68F6X9iJoIUq1QdiZwFkF762uNNnUHnnP3U1qsd0qTKG0EtbW1lJaWUgmMTbFfJcGKO7W1tQnd79xzt4rTzJkz2XfffZkGjE6x3zTgEGDGjBnss88+LR73qbrl/OLO5NfujWuOyLt6ZvfM15Vn4xybKpfvRWk/0jGO4B7gcYIG4gmNyj9395WbGF/alZSUMKS4OOgdlOKPe3IsRungwRQXFydsz+UqTunuNTL95Q84/c9zkm7b4uELOa+iopURZkc2+tO3hT77WlFMsqnZSefc/VN3X+buJ7n7m8DXBJ+l3cysb9YijMjMGF9Rwbx4nEsJAm2sodfQ/Hic8RUVefftan0ii8USYm+wPpGVlCRNZADZEPS/AAAO0klEQVTz3lxJvwlTkyaB6olHccnEo9g87Eo7btw4mrsjzJVs9KdXn32RDUUZWfxDYBKwPfABsBNQDwzJbGitV1ZWRk1NDddUVfFEku6X88Pul2PGjMl1qAkaEll5eTmX0nz31/nxONVJEtk9s9/ikgcXJT32GxOPajPz1mSjP7367Is00VIjAvAS0BNYED4/AJgcpQEiXY8ojcUN2nJj28b0Gnlw/jtJG4C/e8rVGe+BlAnZ6D2VrR5aIrlGGnsNzfVvE0Is/LkmysHT9WhNImgQj8e9trbWZ8yY4bW1tW3mjzlqIrvuny832wso0z2QMq2Qew2JpFPURBBl3oBPzKwbMAO428w+ANZu6p1IprXVxjYzo6ysjDFjxiTtNfLPxe9zxl/mJ7xutz5b8fA5o4CgBxK03TrwbFTxteVqRJF0i5IIjgFWAecBJwNbAb/PZFCSmMieW/oRJ1fPTtivV7fOzL1sww6nbb0O3MyorKxkxIgR3HD99ZzReM6lQYOoPv98xowZs0kN/tk4h0hbkWocwXjgOYK2gbTeAZjZYcAfgQ5Atbtfm2r/TK5Qlu9umPYKf3z61YTyrbt3pubS5CMOvA30k4/Ks9CfPhvnEMmFdIwj6EPwYT3YzBYCzxMkhlm+CeMIzKwDcDPB/EXvAHPM7GF3r9vYY7ZHT9T+h3F3zUsorzh4IOcetEvK125qD6R8ko0qvrZajSiSLs0mAne/AMDMOhEsTPMDgplHq8zsE3ff2L+cvYCl7v56ePx7CaqflAiAyx9azJ2z3kwo36t/EfeP+37k46gOXESiitJGsDmwJUHbwFbAe0DyDuvR7AC83ej5O8CITTheu3DLM68x8Z8vJ5SfPrIfv/1h64dsqA5cRKJqNhGY2WSCQWOfA7MJqoYmufvHm3jO5qqsm55/LOG0QX375t1A5rS58alXuPGpxDaAa47blZP22rTfu6UeSCIikPqOoC/QGXgVeJfgm/snaTjnO8COjZ73IbjL2IC7TwYmQ9BYnIbz5pUHF7zDefe9lFA+6YTdOW5on7SeS3XgIpJKqjaCwyz42jiEoH3gfKDUzFYSNBj/diPPOQfYxcz6EySYE4GfbeSx2pz/9/SrXD/tlYTyv5SNYNQuvXIQkYgUupRtBOHItMVm9gnwafg4iqDBd6MSgbuvNbNzgCcIuo/e5u61G3OstuSYm5/jpbcTb6geOOsHDO37nRxEJCISSNVGcC7BncBIYA1h11HgNjatsRh3fwx4bFOO0VaMv3cB/3gxoeaLR385itIdtspBRCIiG0p1R9AP+Btwnru/n51w2o9xd83lidrlCeV/PPF7HPO9HXIQkYhIcqnaCPJz5ZI8d/P0pVz3xJKE8vvG7s2IAfk1lYOICEQbRyAtcHdOqJzFnGWJPWsfOnsku+/YIwdRiYhEo0SwCdydg2+YwdIPvkjYNvPXB7BjUdccRCUi0jpKBBvB3Tn+1lnMezPxDkAJQETaGiWCVojHnZOrZzPr9cT5+x8+ZyS79VEVkIi0PUoEEcTjzoQHFnL/3HcStv37wv3ZqecWOYhKRCQ9lAhSWL02zsDLHk+67dmLDqDPd1QFJCJtnxJBEs0lgL5FXXn4nJH06NopB1GJiGSGEkEjq9fGGXfXXKYv+TBhW82lB7F19y45iEpEJLOUCEL/WPAu4+97MaF83mWj6dmtcw4iEhHJjoJOBGvXxVm1Nk63zpsxddG3s2h8t/cWPHDmSLbq2jGH0YmIZEdBJoKvV6/jlCmzmffmx4wZ2Z/Lf1hCxcEDOWjw1hzzvR3YvFOHXIcoIpI1BZUIvvxmLSdOfoFF7366vuyF11ewLu4Ub7clxdttmcPoRERyoyASweer1nD8LbNYsvzzDcoPGrw1k38+nA4xLdsoIoWr3SeCeW+u5Me3zNqg7PDSbbnppD3o2CGWo6hERPJHu08EO/Xcgs07duDrNes4evftmXTC7mymBCAisl67TwS9unXmoXNGsnPvbsRUBSQikqDdJwKAgdt0z3UIIiJ5S3UkIiIFTolARKTAKRGIiBQ4JQIRkQKnRCAiUuCUCERECpwSgYhIgVMiEBEpcObuuY6hRWb2IfBmruNohV7AR7kOIk/p2jRP16Z5ujbNS3VtdnL33i0doE0kgrbGzOa6+/Bcx5GPdG2ap2vTPF2b5qXj2qhqSESkwCkRiIgUOCWCzJic6wDymK5N83Rtmqdr07xNvjZqIxARKXC6IxARKXBKBGlmZheYmZtZr/C5mdlNZrbUzBaa2dBcx5htZnadmb0c/v4PmlmPRtsuDq/NEjM7NJdx5pKZHRZeg6VmNiHX8eSSme1oZtPNrN7Mas3sV2F5kZlNM7NXw3+/k+tYc8XMOpjZAjN7NHze38xmh9fmPjPr1JrjKRGkkZntCBwMvNWo+HBgl/AxFrglB6Hl2jSg1N13A14BLgYwsxLgRGAIcBjwJzPrkLMocyT8nW8meK+UACeF16ZQrQXOd/diYG/g7PB6TACedvddgKfD54XqV0B9o+cTgRvCa/MxUNaagykRpNcNwK+Bxg0vxwB3euAFoIeZbZeT6HLE3Z9097Xh0xeAPuHPxwD3uvs37v4GsBTYKxcx5thewFJ3f93dVwP3ElybguTu77v7/PDnzwk+8HYguCZ3hLvdARybmwhzy8z6AEcC1eFzAw4E/hbu0upro0SQJmZ2NPCuu7/UZNMOwNuNnr8TlhWqMcDj4c+6NgFdh2aYWT9gD2A2sI27vw9BsgC2zl1kOXUjwRfOePi8J/BJoy9brX7/FMSaxeliZk8B2ybZdClwCXBIspclKWt3XbVSXRt3fyjc51KC2/67G16WZP92d20i0HVIwsy6AX8Hxrv7Z8EX38JmZkcBH7j7PDPbv6E4ya6tev8oEbSCu49OVm5muwL9gZfCN2sfYL6Z7UWQnXdstHsf4L0Mh5p1zV2bBmZ2GnAUcJB/22e5IK5NBLoOTZhZR4IkcLe7PxAWLzez7dz9/bB69YPcRZgzI4GjzewIoAuwJcEdQg8z2yy8K2j1+0dVQ2ng7ovcfWt37+fu/Qj+sIe6+3+Ah4Gfh72H9gY+bbi9LRRmdhhwEXC0u3/VaNPDwIlm1tnM+hM0qNfkIsYcmwPsEvb86ETQgP5wjmPKmbDOewpQ7+6TGm16GDgt/Pk04KFsx5Zr7n6xu/cJP2dOBP7l7icD04Hjw91afW10R5B5jwFHEDSEfgWcnttwcuJ/gc7AtPCO6QV3P8Pda83sfqCOoMrobHdfl8M4c8Ld15rZOcATQAfgNnevzXFYuTQSOBVYZGYvhmWXANcC95tZGUHPvJ/kKL58dBFwr5ldBSwgSKSRaWSxiEiBU9WQiEiBUyIQESlwSgQiIgVOiUBEpMApEYiIFDglAkkLM9vWzO41s9fMrM7MHjOzgWa2f8MMiblmZr83s5QD39J0nh5mdlYajvOMmaV1nd5UxzSzv5nZgBSv7WRmM8xM3c7bGSUC2WThAKAHgWfc/bvuXkLQ73ub3Ea2IXe/3N2fysKpegCtSgThgMOc/T2a2RCgg7u/3tw+4YR4TwM/zVpgkhVKBJIOBwBr3P3WhgJ3f9HdZ4ZPu4XfNl82s7vDxIGZXW5mc8xssZlNblT+jJlNNLMaM3vFzPYJy7ua2f3hugb3hfOvDw+3HWJms8xsvpn9XzhPzQbM7M9mdnz48zIzuyLcf5GZDU6y/2Nmtlv48wIzuzz8+Uoz+4WZdTOzpxsdo2HG0GuB75rZi2Z2XfiaC8PfdaGZXRGW9bNgzv0/AfPZcJqJprEk/H5mdng4IK9hn/3N7JGo16OJkwlHo5rZThbMa9/LzGJmNtPMGubR+ke4r7QjSgSSDqXAvBTb9wDGE8y1P4Bg5CjA/7r7nu5eCmxOMBdRg83cfa/wdb8Ny84CPg7XNbgSGAZgwSJAlwGj3X0oMBeoiBD3R+H+twAXJNk+A9jHzLYkGPncEPcoYCawCvhReIwDgOvDZDYBeM3dv+fuF4YforsQTDf9PWCYme0bHmsQwTTle7j7m8mCTPH7TQP2NrMtwl1/Cty3kddjJOH/YRjHROBW4Hygzt2fDPdbDOzZwrGkjVFdn2RDjbu/AxBOGdAPeBY4wMx+DXQFioBa4JHwNQ0Tjc0L94fgA/iPAO6+2MwWhuV7EySZ58Kbik7ArAhxNT7HcUm2zwTOBd4ApgIHm1lXoJ+7L7FgYrQ/hB/qcYKpf5NVhx0SPhaEz7sRJIa3gDfDdSpSSfr7hVNT/BP4oZn9jWCO+l8D+yXbv4VzbAd82PDE3avN7CfAGQTJq6F8nZmtNrPu4VoB0g4oEUg61PLthFfJfNPo53XAZmbWBfgTMNzd3zaz3xHMptj0Nev49n3a3DzEBkxz95NaGXeyczQ2BxgOvE7w7bsXUM63dz8nA72BYe6+xsyWNfkdGsd3jbtXblAYzLX/ZYQ4U/1+9wFnAyuBOe7+eXhX0trr8XXj2MOE17CAUDeg8Yd+Z4K7IWknVDUk6fAvoLOZlTcUmNmeZrZfitc0fOh8FNZfp0okDZ4FTgiPXwLsGpa/AIw0s53DbV3NbGArf4cEYePo2+E5XyC4Q7gg/BdgK4K54deY2QHATmH550D3Rod6AhjTUE9vZjuYWWsWVUn1+z0DDCVIUPdF2L859cDOjZ5PJFg34nKgqqHQzHoCH7r7mlbEL3lOiUA2Wbi+wI8Iqk5eM7Na4HekmBPd3T8h+IBZRNAAOSfCqf4E9A6rhC4CFhJM6/0h8F/AX8NtLwAJjb8baSawPJw+eybBt+SGRHA3MNzM5hLcHbwM4O4rCKplFpvZdWH9+j3ALDNbRLCkYHciSvX7hbO1Pkqw3vGjLe2fwlRgf4Awge8JTHT3u4HVZtYwa+4BBDPqSjui2UelzbBgkfeO7r7KzL5L0JVxYPjNXTaBmW1OMKf9yFRTgZvZA8DF7r4ka8FJxqmNQNqSrsD0sJHWgDOVBNLD3b82s98SNHi/lWwfCxbN+YeSQPujOwIRkQKnNgIRkQKnRCAiUuCUCERECpwSgYhIgVMiEBEpcEoEIiIF7v8DGx3rv2qXAhoAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# add a columns of ones for the y-intercept\n",
     "X_aug = np.concatenate([np.ones((m, 1)), X], axis=1)\n",
@@ -358,10 +440,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 53,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def learningCurve(X, y, Xval, yval, lambda_=0):\n",
@@ -442,9 +522,10 @@
     "    error_val   = np.zeros(m)\n",
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
-    "         \n",
-    "\n",
-    "        \n",
+    "    for i in range(1, m+1):\n",
+    "        theta_new = utils.trainLinearReg(linearRegCostFunction, X[:i, :], y[:i], lambda_)\n",
+    "        error_train[i-1] = linearRegCostFunction(X[:i, :], y[:i], lambda_=0, theta=theta_new)[0]\n",
+    "        error_val[i-1] = linearRegCostFunction(Xval, yval, lambda_=0, theta=theta_new)[0]\n",
     "    # =============================================================\n",
     "    return error_train, error_val"
    ]
@@ -462,9 +543,41 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 54,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "# Training Examples\tTrain Error\tCross Validation Error\n",
+      "  \t1\t\t0.000000\t205.121096\n",
+      "  \t2\t\t0.000000\t110.302641\n",
+      "  \t3\t\t3.286595\t45.010231\n",
+      "  \t4\t\t2.842678\t48.368911\n",
+      "  \t5\t\t13.154049\t35.865165\n",
+      "  \t6\t\t19.443963\t33.829961\n",
+      "  \t7\t\t20.098522\t31.970986\n",
+      "  \t8\t\t18.172859\t30.862446\n",
+      "  \t9\t\t22.609405\t31.135998\n",
+      "  \t10\t\t23.261462\t28.936207\n",
+      "  \t11\t\t24.317250\t29.551432\n",
+      "  \t12\t\t22.373906\t29.433818\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "X_aug = np.concatenate([np.ones((m, 1)), X], axis=1)\n",
     "Xval_aug = np.concatenate([np.ones((yval.size, 1)), Xval], axis=1)\n",
@@ -491,9 +604,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise regularized-linear-regression-and-bias-variance\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "Regularized Linear Regression Cost Function |  25 /  25 | Nice work!\n",
+      "     Regularized Linear Regression Gradient |  25 /  25 | Nice work!\n",
+      "                             Learning Curve |  20 /  20 | Nice work!\n",
+      "                 Polynomial Feature Mapping |   0 /  10 | \n",
+      "                           Validation Curve |   0 /  20 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  70 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[3] = learningCurve\n",
     "grader.grade()"
@@ -527,10 +661,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 55,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def polyFeatures(X, p):\n",
@@ -560,10 +692,11 @@
     "    \"\"\"\n",
     "    # You need to return the following variables correctly.\n",
     "    X_poly = np.zeros((X.shape[0], p))\n",
-    "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
-    "\n",
-    "\n",
+    "    X = X.flatten()\n",
+    "    for i in range(1, p+1):\n",
+    "        X_poly[:, i-1] = X**i\n",
+    "        # print(np.power(X[i, :], i))\n",
     "\n",
     "    # ============================================================\n",
     "    return X_poly"
@@ -578,9 +711,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 57,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Normalized Training Example 1:\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "array([ 1.        , -0.36214078, -0.75508669,  0.18222588, -0.70618991,\n",
+       "        0.30661792, -0.59087767,  0.3445158 , -0.50848117])"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "p = 8\n",
     "\n",
@@ -614,9 +766,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise regularized-linear-regression-and-bias-variance\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "Regularized Linear Regression Cost Function |  25 /  25 | Nice work!\n",
+      "     Regularized Linear Regression Gradient |  25 /  25 | Nice work!\n",
+      "                             Learning Curve |  20 /  20 | Nice work!\n",
+      "                 Polynomial Feature Mapping |  10 /  10 | Nice work!\n",
+      "                           Validation Curve |   0 /  20 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  80 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[4] = polyFeatures\n",
     "grader.grade()"
@@ -653,9 +826,55 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 58,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Polynomial Regression (lambda = 100.000000)\n",
+      "\n",
+      "# Training Examples\tTrain Error\tCross Validation Error\n",
+      "  \t1\t\t0.000000\t138.846777\n",
+      "  \t2\t\t0.114107\t144.125230\n",
+      "  \t3\t\t106.956580\t70.863286\n",
+      "  \t4\t\t121.740879\t78.372963\n",
+      "  \t5\t\t102.949459\t63.845046\n",
+      "  \t6\t\t97.169857\t59.532632\n",
+      "  \t7\t\t83.326539\t59.585493\n",
+      "  \t8\t\t76.491825\t58.699842\n",
+      "  \t9\t\t71.297176\t59.564455\n",
+      "  \t10\t\t64.350636\t59.731344\n",
+      "  \t11\t\t58.997943\t60.409869\n",
+      "  \t12\t\t57.977080\t57.842195\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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c7NVKGwgEgsVtphKCyWZL6Z30ZgRcV2AtGtSuqYjCXmJ8LJcc2445fxjOvb/tQebOPK58aQGnPTaP/y5Op6jIko4xVak6qz5PxbU27yQiG0XkCmAicJKIrAJO8l6Da4+wBtfZ47Ps2/rWVKRxB4iJKzPZpAdyqVMrlvqJ4VJqGj4S4mI5f8ARzL5tOA+c25OcPYVcM+U7Tnn0c95b9CuFlnSMqRLVdvRR1bFlzNqvA0evZ9HrqiuWqBcbD42PhK0/lTo7PZBD8waJdk+iHPGxMYxObcPZfVsz/cc0npi1mpumLeLR/63i2uOP4uw+rYiJif79t2fPHjZu3EhubsmOsU0kSkxMpHXr1sTHx/sdSthUEDCHKuVo2Ly81FnpgVxaWhFapcTGCGf2bsXpPVvy8dIMHp+1mtve+IHFG7P425nd/Q6v2m3cuJF69erRrl07OzmJcKpKZmYmGzdupH379n6HEzYdcZpDldIZtq2Fgv37fUzPyqW5VQ44IDExwsgeLfjoxsFcMbg9k79az6Qv1vodVrXLzc2lSZMmlmiigIjQpEmTsLlKtWQTLZI7gRZC5s/7TC4oLGLzjlxaWrI5KCLCn0Z24aSuzfj79GXMXH5Iwx9FBEs00SOcvktLNtEixRvnauu+lQS27MyjSKG5FaMdtNgY4dExvenWsgE3TP2eJb+WHCHXGFMRSzbRoklHQGDLvpUE0rKC1Z7tyuZQ1KkVx3OXpNKgdjxXTP62uDq5qVqZmZn07t2b3r1707x5c1q1alX8Oj8/v+IVAJdddhkrV5ZeM9P4x5JNtKhVBxoeAVtW7DO5uI1NQ0s2h6pZ/UReuPQYduYWcMXkb9mVd6iDvJqSmjRpwqJFi1i0aBHjxo3j5ptvLn5dq5braklVKSoqKnMdkyZNolOnTjUVsqkkSzbRJKXzftWfi3sPqG/FaFWhS4v6PHF+X5anZ3PTtO+tHU4NWb16Nd27d2fcuHH07duX9PR0rr76alJTU+nWrRt333138bKDBw9m0aJFFBQU0LBhQ8aPH0+vXr0YNGgQmzdvLudTTHWyqs/RJOVoWDMHigohxg2Pnh7IpXZ8LPVr21ddVY7v3JQJZ3Tjr+8t5Z4Pl3HX6aV3gBrp/vbBUpalZVfpOru2rH/Q+2vZsmVMmjSJp59+GoCJEyfSuHFjCgoKOP744zn33HPp2rXrPu8JBAIMGzaMiRMncsstt/DCCy8wfvz4Q94Oc+DsyiaaJHeCwjzYvq54UkYglxYNrUFnVbt4UDsuO64dk75Yx0tfrfM7nMPCkUceyTHHHFP8eurUqfTt25e+ffuyfPlyli1btt97ateuzamnngpAv379WLduXU2Fa0qw091okuINt7D1J2hyJABpgRyrHFBN7jytK79s282E95fSplEdju8cXT1qh9sVW1JSUvHzVatW8eijjzJ//nwaNmzIhRdeWGp7kuB9HoDY2FgKCuw+m1/syiaaBKs/h1QSyAjkWgec1cRVie5Dlxb1uf7V76q8yMmULTs7m3r16lG/fn3S09P55JNP/A7JVMCSTTRJbAB1mxdXf3YNOvPsyqYaJSXE8fwlx1Av0VWJ3pRtVaJrQt++fenatSvdu3fnqquu4rjjjvM7JFMBieTxO2zwtFJMPsON2nnVLNIDOQz65yz+8dvuXDCgrd+RRbWlaQFGP/0VHVKSeP13g6hTKzJLqJcvX06XLl38DsNUodK+UxFZqKqpNRmHXdlEm5RO7spGlXSvjY11wln9urVswONj+7AsLZubpi2yKtHGlGDJJtqkdIL8HZCdVtyg0zrhrBkndGnGX0d1ZcayTfzzo9J74DbmcBWZ1/qmbMley+mtK0nLagdYVzU16dLj2rMuczfPzVtLu+QkLhxoxZfGgF3ZRJ+QIaIzvAadDWr7P3DS4eQvo7oyonNT7np/KZ/9tMXvcIwJC5Zsok1SCtRuBFtWkh7IpYWN0FnjYmOEx8b24ehm9bhuynesyLAq0cZYsok2Iq4obctK0gM51gGnT+omxPHCpakkJcRyxYsL2LzDqkSbw5slm2iU0gm2umK05tYBp29aNKjN85ccw7Zd+Vw1eQE5+YV+hxQRMjIyGDNmDEceeSRdu3Zl5MiR/PTTTxW/8RCsW7eO1q1b79ebdO/evZk/f36Z73vxxRe5/vrrAXj66ad56aWXSl139+7lDym+bt06Xn311eLXCxYs4MYbbzyQTQh7lmyiUUon2J3Jnh1brHKAz7q3asBjY/vw468Bbn5tEUVWJbpcqspvf/tbhg8fzs8//8yyZcu499572bRp3xFSCwurNnG3a9eONm3aMHfu3OJpK1asYMeOHfTv379S6xg3bhwXX3zxQX1+yWSTmprKY489dlDrCleWbKKRVyOtvW60YrQwcFLXZtx5Wlc+XprBfR+vqPgNh7HZs2cTHx/PuHHjiqf17t2bIUOGMGfOHI4//njOP/98evToAcC//vUvunfvTvfu3XnkkUcA2LVrF6eddhq9evWie/fuvPbaawCMHz+erl270rNnT2677bb9Pnvs2LFMmzat+PW0adMYO3YsAB988AEDBgygT58+nHjiifslP4AJEybw4IMPArBw4cLiYQ2efPLJ4mXWrVvHkCFDijsQ/fLLL4tjmzt3Lr179+bhhx9mzpw5jBo1CoBt27Zx1lln0bNnTwYOHMiPP/5Y/HmXX345w4cPp0OHDmGfnKzqczTyaqQdFZNmVzZh4vLj2rFu6y7+8/ka2iUnMbb/EX6HVLH/joeMxVW7zuY94NSJZc5esmQJ/fr1K3P+/PnzWbJkCe3bt2fhwoVMmjSJb775BlVlwIABDBs2jDVr1tCyZUs+/PBDwA0zsG3bNt555x1WrFiBiJCVlbXfus877zz69OnD448/TlxcHK+99hpvvPEG4MbI+frrrxERnnvuOe6//34eeuihMuO87LLLePzxxxk2bBh/+MMfiqc3bdqUGTNmkJiYyKpVqxg7diwLFixg4sSJPPjgg0yfPh2AOXPmFL/nrrvuok+fPrz77rvMmjWLiy++mEWLFgHu6mv27Nns2LGDTp06cc011xAfH561T+3KJho1aE1BbB2Okl/tnk2YEBHuOr0rwzulcOe7S5i7yqpEH4z+/fvTvn17AObNm8dvf/tbkpKSqFu3LmeffTZz586lR48e/O9//+P2229n7ty5NGjQgPr165OYmMiVV17J22+/TZ06dfZbd/PmzenWrRszZ85k0aJFxMfHF99r2bhxI7/5zW/o0aMHDzzwAEuXLi0zxkAgQFZWFsOGDQPgoosuKp63Z88errrqKnr06MHo0aNLHRahpHnz5hWvY8SIEWRmZhIIBAA47bTTSEhIIDk5maZNm5Z6xRUu7MomGomwPakdR+X/SksrRgsbcbExPD62D6Of/oprX/mOt649lqOb1fM7rLKVcwVSXbp168abb75Z5vzQYQbK6tfx6KOPZuHChXz00UfccccdnHzyyfz1r39l/vz5zJw5k2nTpvHEE08wa9as/d4bLEpr1qxZcREawA033MAtt9zCGWecwZw5c5gwYUKZMapqmc0NHn74YZo1a8YPP/xAUVERiYkV/3+Wtp3B9SckJBRPC/chFOzKJkqlxx9Bx5hfrUFnmKmXGM/zlx5DYq1YLpv0LVt25PkdUlgZMWIEeXl5PPvss8XTvv32Wz777LP9lh06dCjvvvsuu3fvZteuXbzzzjsMGTKEtLQ06tSpw4UXXshtt93Gd999x86dOwkEAowcOZJHHnmkuBiqpHPOOYePPvqI1157jTFjxhRPDwQCtGrVCoDJkyeXuw0NGzakQYMGzJs3D4ApU6bss54WLVoQExPDyy+/XFzRoV69euzYsaPU9Q0dOrR4HXPmzCE5OZn69euXG0M4smQTpdZKa1rINiSv9B+w8U+rhrV5/pJUMnflceVLViU6lIjwzjvvMGPGDI488ki6devGhAkTaNmy5X7L9u3bl0svvZT+/fszYMAArrzySvr06cPixYvp378/vXv35h//+Ad33nknO3bsYNSoUfTs2ZNhw4bx8MMPl/r5DRs2ZODAgTRr1qy4uA7czfjRo0czZMgQkpOTK9yOSZMmcd111zFo0CBq195blH3ttdcyefJkBg4cyE8//VR8pdazZ0/i4uLo1avXfrFNmDCBBQsW0LNnT8aPH19hsgtXNsRAlJr48EOMD9wNV86C1mXfcDX++WRpBuNeWcgp3Zrz5Pl9iYnxv6cHG2Ig+tgQA6Zafb/bG6J460p/AzFl+k235vzp1C78d0kG939i35OJblZBIAoVFinf72pIQUI8cVusXUc4u3JIe9Zm7uLpz36mXZM6jImEKtHGHAS7solCW3bkkV8Uw46ktsVDRJvwJCL87YxuDOmYzJ/eWcyf31nMtl35vsYUyUXrZl/h9F1asolC6YEcAPIbdbRitAgQHxvD0xf24+JB7Zj27S8Mf2A2L8xby57CoorfXMUSExPJzMwMq4OUOTiqSmZmZqWqV9cEK0aLQsEROmNSOsPGT2BPLsSHxw/OlC4pIY4JZ3TjggFHcPf0Zdw9fRlTvlnPX0Z1ZXinpjUWR+vWrdm4cSNbtlij02iQmJhI69at/Q4DsGQTldK8ZFO7VRf4rggyV0Pz8nudNeGhY7N6vHR5f2at2Mzfpy/j0knfMqJzU+48rQsdUupW++fHx8fvU+XXmKpixWhRKCOQQ2J8DEmturoJVkkgoogIJ3Rpxqc3D+NPIzszf+02Tn74c+6ZvoxAzh6/wzPmoPiSbETkZhFZKiJLRGSqiCSKSHsR+UZEVonIayJSy4/YooEbobM20qQjSAxstUoCkahWXAxXDz2S2bcN59x+rXn+i7WMeHAOr36zgUIbqsBEmBpPNiLSCrgRSFXV7kAsMAa4D3hYVTsC24Erajq2aJEeyKV5/UR3n6ZRO9hilQQiWUq9BCae05MPrh9Mh5Qk/vTOYkY9Po+v12T6HZoxleZXMVocUFtE4oA6QDowAgj2wDcZOMun2CJeRiB37zg2KZ0t2USJ7q0a8PrvBvHE+X0I7M5nzDNfc92U7/hl226/QzOmQjWebFT1V+BBYAMuyQSAhUCWqga7LN0ItCrt/SJytYgsEJEFVmNmf4VFSkZ27t5xbJKPdhUECsO3N1hTeSLCqJ4tmXnrcG4+8WhmrtjECf/6jIc+XcnufPuOTfjyoxitEXAm0B5oCSQBp5ayaKmF0qr6jKqmqmpqSkpK9QUaobbuzKOwSGnRwOv8L6UTFO2B7Wv9DcxUqdq1YrnpxI7MunU4p3ZvzuOzVjPiwc945/uNNvS0CUt+FKOdCKxV1S2qugd4GzgWaOgVqwG0BtJ8iC3ipXvVnouvbLxRO2u0KG3bGshYUnOfdxhr2bA2j47pw1vXDKJp/QRufu0Hznn6Sxb9sv9IlMb4yY9kswEYKCJ1xI0AdAKwDJgNnOstcwnwng+xRbz0LNd7QPPQYjSomZ4ECvJgzkR4cgA8dyKklT5miKl6/do25t1rj+OBc3vyy7YcznryC259/Qc2Zef6HZoxgD/3bL7BVQT4DljsxfAMcDtwi4isBpoAz9d0bNEgeGXTMliMllAP6req/iub9V/B04Nhzj+hy+lQpwlMuwB2bq7ezzXFYmKE0altmH3bMMYNO5IPfkjj+Afn8OTs1eTusTFzjL98qY2mqnepamdV7a6qF6lqnqquUdX+qnqUqo5WVRvC8CBkZOeSEBdDwzohI3SmdKq+ZJOTBR/8HiadAgW5cMFbcO4LMGYK7M6E1y+GAn87ljzc1EuMZ/ypnZlxy1AGH5XMA5+s5KSHP+PjJRnW55nxjfUgEGXSsnJo0SBx3zHQkzvB1lVQVIUdO6rC0nfhyf7w3WQYdD1c+zV0PNHNb9kbznwCNnwF//2DW97UqLZNknjm4lReuWIAteNjGffKQs5/9huWpgX8Ds0chizZRJkMr/eAfaR0gj27IHtj1XxIYCNMOx/euATqNoOrZsFv/gG1kvZdrse5MPhmWPgifPtc1Xy2OWCDOybz0Y1D+PuZ3Viekc1pj83jgue+ZubyTVZzzdQY64gzyqQHchnQvvG+E4trpP0EDQ9hcK6iQpc0Zt5Z8u9gAAAgAElEQVQNWgQn3wMDroHYcn5GI/4Cm5bBx+NdA9P2Qw7+881Bi4uN4aJB7TijVyumzF/PS1+u54rJC2ifnMRlx7XjnL6tSUqww4GpPnZlE0UKi5RN2SG9BwQlB5PNIXTIuWkpPH8y/PeP0GYAXPsVHHtD+YkGICYWznkWGndw92+2rz/4GMwha1AnnmuHH8Xc24/n0TG9qZ8Yx1/fW8rAf87k3o+W86tXm9GYqmbJJopk7syjoEhpXrIYLakJ1Ek+uOrPe3Lgf3+D/wyF7evg7Ofgwrdcn2uVldgAxkx1V0bTzoe8nQceh6lS8bExnNm7Fe9edxxvXXMsQ49O4fl5axl6/2yum/IdC9dvs8oEpkrZdXMUCY5j06J+KQOlpXQ68CGi13wG03/vGmn2vsAVm9VpXPH7SpN8FIx+AaaMhnevgdGTIcbOdfwmIvRr24h+bRvxa1YOL325jqnzN/Dh4nR6tWnI5ce1Y2SPFsTH2ndlDo39gqJIhjcc9H7FaOAlmxWVqxW2exu8ey28dIZ7ffH7cNZTB59ogo46EU66G5a/D3MfPLR1mSrXqmFt7hjZha/uOIG/n9mN7Jw93DRtEUPum81Tc1azfZdVYTcHz65sokhaVrCrmtr7z0zuBLlZsGsL1C1jmGFVWPyGu5mfG4Aht8LQP0B8Kes7WIOuh4zFMPsf0LQrdBlVdes2VSIpIY6LBrXjggFtmfPTZl6Yt477P17JYzNXcXbf1lx+XDuOalrP7zBNhLFkE0WCDTobhTboDErxuq3ZsrL0ZLN9HUy/BX6eCa36wemPVc9Q0iJw+qOu3c87v4PGM6BZ16r/HHPIYmKEEZ2bMaJzM1ZkZDNp3jreXLiRV7/ZwLCjU7h8cHuGdkzet02XMWWwYrQo4kboTCz9nz+ls/tbskZaYQF8+Tg8NQh++QZOvR+umFE9iSYovrbrYaBWXZg6xhXbmbDWuXl97ju3J1+NH8GtJx3NsvRsLnlhPic9/DmvfrOBnHzrDseUz5JNFEnPytnbAWdJ9VpArXr7DhGd9j08ezx8eie0HwbXfQMDfueqK1e3+i3h/16BHemucaiNtxMRmtRN4IYTOvLF7SP413m9SIiL4U/vLObYiTN54JMVZASs409TOks2USQ9kLu3A86SRPZWEsjfBZ/8GZ4dATs3wXkvwdip0KB1zQbc5hgY9Qis/Rw+/XPNfrY5JLXiYji7b2um3zCY1383iP7tG/PUnJ8ZfN8sbpr2PT/YEAemBLtnEyWKvAadZV7ZgEs2y6fDkwMhsAH6XQYnToDaDWsqzP31uQA2LYGvn4Jm3aHvRf7FYg6YiNC/fWP6t2/MhszdTP5qHa99+wvvLUpjSMdk7jq9G0c1ret3mCYM2JVNlNjqNehsUW6y6Qx5AYhPhMv+C6c/4m+iCTrp79BhOEy/GTZ843c05iAd0aQOfxnVla/uGMGfR3Zh0S9ZnPLI59wzfRnZuXv8Ds/4zJJNlNg7Qmc51ZRTL4Nznodx86DtsTUUWSXExsG5k1wx3msXQuBXvyMyh6BeYjxXDe3AnNuGMzq1Nc9/sZYRD87h9QW/WMefhzFLNlEiPVBihM7SJNRzPTHHJdRQVAegTmN332jPbtelzR7royvSNambwD/P7sn71w3miMZ1+OObP/Lbf9uQ1YcrSzZRYu+VTTnJJtw17QJnPwvpi+D9G2wMnCjRo3UD3hx3LP86rxdpWW7I6j+88QNbdtj4iIcTSzZRIiOQS624GBon1fI7lEPTeSQcf6fryeDLx/yOxlSRmBjh7L6tmX3bcH43rAPvLvqVEQ/O4bm5a9hTWIWD+pmwZckmSqSV16Az0gy9DbqeBTPuglUz/I7GVKG6CXHccWoXPvn9UPq1a8Q9Hy7nlEc+5/OftvgdmqlmlmyiREYgJ7KL0EKJuI4/m3eHN69wXduYqNIhpS4vXtafFy5NpbBIufiF+Vz10gI2ZO72OzRTTSzZRIn00oaDjmS1kmDMq66m2tQxkGM3laPRiM7N+OTmofzxlE58sXorJz78GQ99upLd+dajRLSxZBMFKtWgMxI1PALOe9l1EvrWlW7wNRN1EuJiuXb4Ucy6dTgjuzfn8VmrOeGhz/jghzQbwC2KWLKJAlt35bGnUGkZbckGoN1xrnPQ1TNg5t/8jsZUo+YNEnlkTB/eGDeIxkm1uGHq9/zfM1+zLC3b79BMFbBkEwXSvXFs9hsOOloccwWkXg5fPAo/vu53NKaaHdOuMe9fP5h7f9uDVZt2MOrxufzl3SVk7bbB2yKZJZsoEBVtbCpyyn1wxLGu/c2v3/kdjalmsTHC+QOOYPZtw7loYFumfLOe4Q/O4ZWv11NovRBEJEs2UaB4OOhoTjZxtVzv1EkpMO0C2LHJ74hMDWhYpxZ/O7M7H900hM7N63Hnu0sY9fg85q+1MZAijSWbKJAeLQ06K1I3xdVQy9nu+lArsBboh4vOzesz9aqBPHl+XwK78znvP19x49Tvi7tpMuHPkk0UKHeEzmjToqdrg7NxPnx4i3VpcxgREU7r2YKZtw7nxhM68vHSDEY8+Bn3TF/Gr1mWdMKdjWcTBdIDOTSvH8VFaCV1Pxs2LYW5D0JREfS7FNr0d41BTdSrXSuWW046mtH9WvPgpyuZ9OU6Jn25jlE9W3DVkA50b9XA7xBNKSzZRIH0QC6pbRv5HUbNOv7PkJcN370MP7wKjdpDrzHQ8zxo3MHv6EwNaNO4Do+O6cMfT+nMpHlrmeYN2jaoQxOuHtqBYUenEBNjJyDhQiK50VRqaqouWLDA7zB8VVSkdPrLf7lySAduP6Wz3+HUvNxsWP4B/DAV1s0DFNoMgJ7/B91+64YuMIeF7Nw9TJu/gRfmrSMjO5ejmtblqiHtObN3KxLjY/0OL6yIyEJVTa3Rz7RkE9k278il/z9mcveZ3bh4UDu/w/FXYKNrh/Pja7BlBcTWgqN/Az3HQMeTXY02E/XyC4r4cHEaz36+lmXp2STXTeDSY9tywYC2NIr2SjSVZMnmAFmygR83ZnHGE1/w7MWpnNS1md/hhAdVNybOD6/Bkjdh1xao3Qi6n+MST+tUu79zGFBVvvw5k2c+X8NnP22hdnwso1Nbc8Xg9rRtkuR3eL7yI9nYPZsId1g06DxQItCyj3uc/Hf4eTb8OA2+fwW+fQ4aH+mK2XqeB43b+x2tqSYiwnFHJXPcUcmszNjBc3PXMHX+Bl7+ej2ndGvOlUM60O9wu9fpI1+ubESkIfAc0B1Q4HJgJfAa0A5YB5ynqtvLW49d2cCLX6xlwgfLWHDniSTXDcPhnsNJbgCWve+K2dbNddOOGOTd3znLXf2YqLYpO5fJX65jyjcbCOTsoV/bRlw1pD0ndW1O7GFUmeCwKUYTkcnAXFV9TkRqAXWAPwHbVHWiiIwHGqnq7eWtx5IN/PO/y5k0bx0r7znl8GhnU1WyNuy9v7P1J+/+zinQaywcdaLd34lyu/IKeGPBLzz/xVp+2ZZD2yZ1uHJwe87t14bassfVdMzb4U5Q8rJBi6B5T0hK9jv0KnFYJBsRqQ/8AHTQkA8XkZXAcFVNF5EWwBxV7VTeuizZwI1Tv2fRL1l8/sfj/Q4lMqlC2vfwwzR3f2d3JtRu7O7v9BoDrfrZ/Z1IUVQE+Ttdcsj1kkVetpcwdoRMDyaSbIpyA+wIbGN39nZqFe6knuRQi3LG0mnUDlqlQutj3L2/5j0gLvJKFA6XZNMbeAZYBvQCFgI3Ab+qasOQ5bar6n7lGiJyNXA1wBFHHNFv/fr1NRJ3uDrv6a9A4PXfDfI7lMhXuAdWz3T3d1Z8BIV50OQo6H4u1G0K6N4eC1S910Uhz0v+LW0ee19r0b7zJNYV5dVp7BJenUbe38aQUD88k15hgTuY52yD3dtcV0I53t89OW4MIi2EogLvUVjKtCL3t9xp3vuC8zXkdd7OvQmECo5nEuP2ZUJ9SPT+JtRDE+uzJb8WCzMKWZyp5EgdOrVtxdCeR9KyaVP3XaV9DxsXuMeONLe+2FruiieYfFqnQsO24fldhThckk0q8DVwnKp+IyKPAtnADZVJNqHsygaG3D+Lfkc04pExffwOJbrkZMGy91wx2/ovauADhXIPlDFxXiJqsjcB7ZOYgn+b7H1eu5Eb6bQyVN0Be/e2vcli9/a9ySM0kYQ+zw1Ubv0xcXsfEgsxwUdwWoz3PHbvXwmZH1y+tGm16kFCvX2Sx97n+yYVaiVVmAjWbNnJ8/PW8ubCjeQVFDGic1MuGtiWdslJNKlbi3oJcUh2Gvy6YG/ySfseCrwuc+oke8mnn/vbsq+LIYwcLsmmOfC1qrbzXg8BxgNHYcVoByTYoPOKwR0Yf+ph2KCzpuRs9zr9FO9AJe7gGDxoFU8L+Ssx+08rbV7oga+o0B28d2fuPeiX9rfktMJyxnlJaLDvFVLtxhAbXyKpeH+1nJFQExu45BWa6PZ73mjv89qNvAN7LMREZheMmTvzePnr9bz81Xoyd+3dx7ViY2hStxbJdRNoUrcWTZISaFonhqNkA+1zV9By52Iabl9MYtZq7x0CKZ33Jp9WqdC0i0uUPjksqj6raoaI/CIinVR1JXACrkhtGXAJMNH7+15NxxZpMnfluxE6G1q152pVU7XUYmLdwftAej1QhfxdFSek3dtcEtu6yhU9BZND0677XiGV9jyxYeWvkKJIk7oJ/P7Eoxk37Ejmr93G1p15ZO7MZ+su9zdzZx6Zu/JZtWknW3bmkV8A0Nl7jKY+O+kVs4aBtdbQb9vPdNv6HvW+fwWA/Jg6bGvQlZ0pfShsmUqtdsfQMKUNDWrHR20XO379gm4Apng10dYAl+F6oH5dRK4ANgCjfYotYmR4bWwOq044zb5EIKGuezQ8wu9oolJifCxDj04pdxlVZWdegUtCu/LYujPfS0h92bIrn1d25pG5I4+EHetovWsZHfesoHfmarpue4H4n54FYKMm801sN075y3thf8/nYPiSbFR1EVDaJdwJNR1LJEsrHjQtSoeDNiZCiAj1EuOplxhPu+TyeidwFXkKi5Ttu/NZk5VF3i+LkF8XkrTlezprYVQmGrAeBCJa8MqmhRWjGRNRYmOE5LoJJNdtBq1/A/zG75CqXWTeuTOAu7KpFRtD4zrWANEYE94s2USwjEAuzRokRO0NRWNM9LBkE8HccNB2v8YYE/4s2USw9ECO9fZsjIkIlmwiVFGRsimQZ1c2xpiIUGGyEZFYEXmgJoIxlbdtdz75hUV2ZWOMiQgVJhtVLQT6ifVfH1bSs7wGnZZsjDERoLLtbL4H3hORN4BdwYmq+na1RGUqlO416GxpxWjGmAhQ2WTTGMgERoRMU8CSjU+Cw0HblY0xJhJUKtmo6mXVHYg5MOmBXOJjhSZJ1qDTGBP+KlUbTURai8g7IrJZRDaJyFsi0rq6gzNlywjk0LxBojXoNMZEhMpWfZ4EvA+0BFoBH3jTjE/SArm0qG/3a4wxkaGyySZFVSepaoH3eBEov89tU60yArnWAacxJmJUNtlsFZELvTY3sSJyIa7CgPFBUZGSEci1ygHGmIhR2WRzOXAekAGkA+d604wPiht02qBpxpgIUWFtNBGJBc5R1TNqIB5TCXvHsbF7NsaYyFDZHgTOrIFYTCWlZQVH6LQrG2NMZKhso84vROQJ4DX27UHgu2qJypQrI9sadBpjIktlk82x3t+7Q6Yp+/YoYGpIsEFnclKC36EYY0ylVOaeTQzwb1V9vQbiMZWQnpVDs/rWoNMYEzkqc8+mCLi+BmIxlZQeyLUOOI0xEaWyVZ9niMhtItJGRBoHH9UamSlTurWxMcZEmMreswm2qbkuZJoCHao2HFMRVdegs0V3SzbGmMhR2V6f21d3IKZytu2yETqNMZGn3GI0EfljyPPRJebdW11BmbLtHcfG7tkYYyJHRfdsxoQ8v6PEvFOqOBZTCcFkY1c2xphIUlGykTKel/ba1IAMbzho6/HZGBNJKko2Wsbz0l6bGpBmDTqNMRGoogoCvUQkG3cVU9t7jvfaTq19kBHItQadxpiIU26yUdXYmgrEVE5aVo7drzHGRJzKNuo0YSIjO9dqohljIo4lmwiiql5XNXZlY4yJLJZsIsi2XfnkFxRZVzXGmIhjySaC7G1jY8VoxpjI4luyEZFYEfleRKZ7r9uLyDciskpEXhORWn7FFq6sQacxJlL5eWVzE7A85PV9wMOq2hHYDlzhS1RhrLhBpyUbY0yE8SXZiEhr4DTgOe+14Eb9fNNbZDJwlh+xhbP0QC5xMUJyXWvQaYyJLH5d2TwC/BEo8l43AbJUtcB7vRFoVdobReRqEVkgIgu2bNlS/ZGGkXRr0GmMiVA1nmxEZBSwWVUXhk4uZdFSu8NR1WdUNVVVU1NSUqolxnCVHrAGncaYyFTZwdOq0nHAGSIyEtflTX3clU5DEYnzrm5aA2k+xBbWMgK59Gjd0O8wjDHmgNX4lY2q3qGqrVW1HW4Ig1mqegEwGzjXW+wS4L2aji2cBRt02pWNMSYShVM7m9uBW0RkNe4ezvM+xxNWtu/eQ16BjdBpjIlMfhSjFVPVOcAc7/kaoL+f8YSztCyr9myMiVzhdGVjypFhw0EbYyKYJZsIkZ7tko11wmmMiUSWbCJEelYOcTFCE2vQaYyJQJZsIkRwhM5Ya9BpjIlAlmwihFV7NsZEMks2ESI9kGPj2BhjIpYlmwhQPEJnQ6uJZoyJTJZsIkCwQWfz+nZlY4yJTJZsIkC6jWNjjIlwlmwiQLBBZwsrRjPGRChLNhEgzYaDNsZEOEs2ESAjkGMjdBpjIpolmwiQbg06jTERzpJNBEjPyrU2NsaYiGbJJgJkZFvvAcaYyGbJJsypKmlZOZZsjDERzZJNmMsKNui0cWyMMRHMkk2YSw/YODbGmMhnySbMBXsPsAoCxphIZskmzKUXN+i0YjRjTOSyZBPm0gM5xMYIKfWsQacxJnJZsglz6YFcmtVLsAadxpiIZskmzGUEcq0DTmNMxLNkE+bSA9Z7gDEm8lmyCWNuhM4cWtigacaYCGfJJowFcvaQu6fIitGMMRHPkk0YS8uycWyMMdHBkk0Yy8i24aCNMdHBkk0Y23tlY8VoxpjIZskmjGUEcq1BpzEmKliyCWPWoNMYEy0s2YSx9ECOtbExxkQFSzZhLCOQa/drjDFRwZJNmHINOm04aGNMdKjxZCMibURktogsF5GlInKTN72xiMwQkVXe30Y1HVs4CeTsIWdPoRWjGWOigh9XNgXAraraBRgIXCciXYHxwExV7QjM9F4ftopH6LTeA4wxUaDGk42qpqvqd97zHcByoBVwJjDZW2wycFZNxxZObIROY0w08fWejYi0A/oA3wDNVDUdXEICmpbxnqtFZIGILNiyZUtNhVrj9o7QacnGGBP5fEs2IlIXeAv4vapmV/Z9qvqMqqaqampKSkr1BeizYIPOpvUs2RhjIp8vyUZE4nGJZoqqvu1N3iQiLbz5LYDNfsQWLtKycmlqDTqNMVHCj9poAjwPLFfVf4XMeh+4xHt+CfBeTccWTjKyrUGnMSZ6+HFlcxxwETBCRBZ5j5HAROAkEVkFnOS9PmylB3JpaQ06jTFRIq6mP1BV5wFllQ2dUJOxhCtVJT0rl+M7lVpHwhhjIo71IBCGsnMKyNlTaDXRjDFRw5JNGEoLBAdNs2I0Y0x0sGQThjK8NjZWQcAYEy0s2YShvV3VWLIxxkQHSzZhKD2QQ4xASl0bodMYEx0s2YSh9EAuTeslEhdrX48xJjrY0SwMpQdyaGFFaMaYKGLJJgzZoGnGmGhjySbMqKoNB22MiTqWbMJMdk4Bu/OtQacxJrpYsgkz6dk2aJoxJvpYsgkzewdNs2I0Y0z0sGQTZtKzbIROY0z0sWQTZjK8Bp1N61mDTmNM9LBkE2bSrEGnMSYK2REtzGQEcq1ygDEm6liyCTPpgRzrgNMYE3Us2YQRVSU9kEvz+lYTzRgTXSzZhJHsXGvQaYyJTpZswkhw0DTrhNMYE20s2YSRvcNBW7IxxkQXSzZhZO9w0HbPxhgTXSzZhJH0LGvQaYyJTpZswkh6IJeUegnEW4NOY0yUsaNaGMnItnFsjDHRyZJNGEnLyrHKAcaYqGTJJkwUN+i0ZGOMiUKWbMJEsEFnSytGM8ZEIUs2YWJvtWe7sjHGRB9LNmEi3WvQaZ1wGmOikSWbMJFuDTqNMVHMkk2YSA/kItag0xgTpSzZhImMQA5NrUGnMSZK2ZEtTLhqz1aEZoyJTpZswkR6IJcW9a1ygDEmOoVVshGRU0RkpYisFpHxfsdTU1SV9KwcG8fGGBO14vwOIEhEYoEngZOAjcC3IvK+qi7zN7LSFRUpRaoUqqIKhd7roiLc33LmuelKofd6d34Bu2yETmNMFAubZAP0B1ar6hoAEZkGnAn4mmyOmziLbbvyQxKEUqTV81lHNE6qnhUbY4zPwinZtAJ+CXm9ERhQciERuRq42nuZJyJLaiC2GnHqfSQDW/2Oo4pE07ZAdG1PNG0LRNf21NS2tK2Bz9hHOCUbKWXaftcQqvoM8AyAiCxQ1dTqDqymRNP2RNO2QHRtTzRtC0TX9kTTtpQUThUENgJtQl63BtJ8isUYY0wVCqdk8y3QUUTai0gtYAzwvs8xGWOMqQJhU4ymqgUicj3wCRALvKCqSyt42zPVH1mNiqbtiaZtgejanmjaFoiu7YmmbdmHqFZT1SpjjDHGE07FaMYYY6KUJRtjjDHVLmKTTbR0bSMibURktogsF5GlInKT3zEdKhGJFZHvRWS637EcKhFpKCJvisgK7zsa5HdMh0JEbvZ+Z0tEZKqIREy3FSLygohsDm1bJyKNRWSGiKzy/jbyM8YDUcb2POD91n4UkXdEpKGfMValiEw2IV3bnAp0BcaKSFd/ozpoBcCtqtoFGAhcF8HbEnQTsNzvIKrIo8DHqtoZ6EUEb5eItAJuBFJVtTuuIs4Yf6M6IC8Cp5SYNh6YqaodgZne60jxIvtvzwygu6r2BH4C7qjpoKpLRCYbQrq2UdV8INi1TcRR1XRV/c57vgN3MGvlb1QHT0RaA6cBz/kdy6ESkfrAUOB5AFXNV9Usf6M6ZHFAbRGJA+oQQW3ZVPVzYFuJyWcCk73nk4GzajSoQ1Da9qjqp6pa4L38GtfeMCpEarIprWubiD1AB4lIO6AP8I2/kRySR4A/AkV+B1IFOgBbgEleseBzIhKxHdip6q/Ag8AGIB0IqOqn/kZ1yJqpajq4Ezegqc/xVKXLgf/6HURVidRkU6mubSKJiNQF3gJ+r6rZfsdzMERkFLBZVRf6HUsViQP6Av9W1T7ALiKrmGYf3v2MM4H2QEsgSUQu9DcqUxoR+TOuiH2K37FUlUhNNlHVtY2IxOMSzRRVfdvveA7BccAZIrIOV7Q5QkRe8TekQ7IR2KiqwSvNN3HJJ1KdCKxV1S2qugd4GzjW55gO1SYRaQHg/d3sczyHTEQuAUYBF2gUNYSM1GQTNV3biIjg7gksV9V/+R3PoVDVO1S1taq2w30ns1Q1Ys+cVTUD+EVEOnmTTsDnIS8O0QZgoIjU8X53JxDBFR487wOXeM8vAd7zMZZDJiKnALcDZ6jqbr/jqUoRmWy8G2jBrm2WA69XomubcHUccBHuKmCR9xjpd1Cm2A3AFBH5EegN3OtzPAfNu0J7E/gOWIz7/4+Y7lFEZCrwFdBJRDaKyBXAROAkEVmFG3hxop8xHogytucJoB4wwzsWPO1rkFXIuqsxxhhT7SLyysYYY0xksWRjjDGm2lmyMcYYU+0s2RhjjKl2lmyMMcZUO0s25qCIiIrIQyGvbxORCVW07hdF5NyqWFcFnzPa68l5donp7UTk/INc55eVWOa5KOhsdR8istPvGEx4s2RjDlYecLaIJPsdSCivR/DKugK4VlWPLzG9HVBqsvE6sCyTqlbYIl9Vr1TVSG4caswBs2RjDlYBrkHgzSVnlLwyCZ71ishwEflMRF4XkZ9EZKKIXCAi80VksYgcGbKaE0VkrrfcKO/9sd54H9964338LmS9s0XkVVxjxZLxjPXWv0RE7vOm/RUYDDwtIg+UeMtEYIjXqO5mEblURN4QkQ+AT0WkrojMFJHvvPWeGfJZods6R/aOhTPFa7WPNz01uLyI/ENEfhCRr0WkmTf9SO/1tyJyd1lXDiJyobf/FonIf7x91Fbc+C7JIhLj7ceTveXfFZGF4sa0uTo0bhG5z5v3PxHp78W5RkTO8Ja5VETeE5GPxY0ldVcZMf0h5Dv6mzctSUQ+9LZziYj8X2nvNVFMVe1hjwN+ADuB+sA6oAFwGzDBm/cicG7ost7f4UAW0AJIAH4F/ubNuwl4JOT9H+NOhjri+ihLBK4G7vSWSQAW4DqVHI7rJLN9KXG2xHXTkoLrWHMWcJY3bw5ubJeS7xkOTA95fakXQ2PvdRxQ33ueDKxmbwPp0G0N4Prti8G1FB9c8nNxHcie7j2/P2T7pgNjvefjgustEWcX4AMg3nv9FHCx9/xKXG8BfwD+E/Ke4DbUBpYATULiONV7/g7wKRCPG8NnUch+SAeahLw/tcR2n4w7CRFvu6fjhmk4B3g2JI4Gfv+G7VGzD7uyMQdNXe/UL+EG5Kqsb9WN4ZMH/Iw7qIG7ImkXstzrqlqkqquANUBn3IHsYhFZhBuGoQkuGQHMV9W1pXzeMcAcdZ1PBnvRHXoA8QbNUNXg2CMC3Ot1YfM/3PAWzUp5z3xV3aiqRcCiEtsXlI87IAMsDFlmEPCG9/zVMmI6AegHfOvtkxNwwyKgqs/huj0ZhzsRCLpRRH7AjZXShr37Lx+X4MF9F5+p66yz5PcyQ1UzVTUH15Hn4BIxnew9vsd1i9PZ+4zFuKvV+0RkiKoGytgmE6XKLX82phIewR1UJoVMK8ArovWKjmqFzMsLeV4U8rqIfX+PJTX68bMAAAI0SURBVPtRUtxB/gZV/SR0hogMx13ZlKa04SgORuj6L8BdKfVT1T3ierkubXjl0G0tpPT/tz2qqhUsUxYBJqvqfqM5ikgd9g68VRfY4e2nE4FBqrpbROaExB0aR/H3oqpFJe5Tlfa9lIzpn6r6n1Ji6geMBP4pIp+q6t2V20wTDezKxhwS72z/ddzN9qB1uDNucOOnxB/Eqkd79xuOxJ2tr8R1vHqNuCEZEJGjpeLBzL4Bhnn3L2KBscBnFbxnB+6qoCwNcOP27BGR44G2ldieA/U1rugJyh66eSZwrog0BRCRxiISjOU+3FXcX4FnQ+Le7iWazrhhyA/USd7n1MaNivlFifmfAJeLG58JEWklIk1FpCWwW1VfwQ3gFslDNZiDYFc2pio8hOuFO+hZ4D0RmY87IJZ11VGelbik0AwYp6q5IvIcrkjnO++KaQsVDAOsqukicgcwG3fW/ZGqVtQN/Y9AgVfc9CKwvcT8KcAHIrIAVzy24kA2rJJ+D7wiIrcCH+Lu/+xDVZeJyJ24SgsxwB7gOnEjvh4DHKeqhSJyjohchiuOG+cV/63EJbQDNQ94GTgKeFVVF5SI6VMR6QJ85dWH2Alc6C3/gIgUeXFecxCfbSKY9fpsTBjyisFyVFVFZAyussCZFb2vmmO6FFch4PqKljWmJLuyMSY89QOe8K7gsnDj0RsTsezKxhhjTLWzCgLGGGOqnSUbY4wx1c6SjTHGmGpnycYYY0y1s2RjjDGm2v0/Wj34SdlRdwUAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "lambda_ = 100\n",
     "theta = utils.trainLinearReg(linearRegCostFunction, X_poly, y,\n",
@@ -731,10 +950,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 92,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def validationCurve(X, y, Xval, yval):\n",
@@ -804,8 +1021,17 @@
     "    error_val = np.zeros(len(lambda_vec))\n",
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
-    "\n",
-    "\n",
+    "    # X, mu, sigma = utils.featureNormalize(X)\n",
+    "    # X = np.concatenate([np.ones((y.size, 1)), X], axis=1)\n",
+    "    # Xval -= mu\n",
+    "    # Xval /= sigma\n",
+    "    # Xval = np.concatenate([np.ones((yval.size, 1)), Xval], axis=1)\n",
+    "\n",
+    "    for i in range(len(lambda_vec)):\n",
+    "        lambda_ = lambda_vec[i]\n",
+    "        theta = utils.trainLinearReg(linearRegCostFunction, X, y, lambda_)\n",
+    "        error_train[i] = linearRegCostFunction(X, y, theta, lambda_)[0]\n",
+    "        error_val[i] = linearRegCostFunction(Xval, yval, theta, lambda_)[0]\n",
     "\n",
     "    # ============================================================\n",
     "    return lambda_vec, error_train, error_val"
@@ -825,12 +1051,84 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 93,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1.0\n",
+      "[[        nan -0.38916543 -0.72149541  0.16876064 -0.69803716  0.30354037\n",
+      "  -0.58940525  0.34396872 -0.50824813]\n",
+      " [        nan -0.31677737 -0.80773065  0.20193698 -0.71734245  0.31055382\n",
+      "  -0.592639    0.34512817 -0.50872536]\n",
+      " [        nan  1.32160772  0.43462051  1.11951372  0.07470578  0.83904444\n",
+      "  -0.1563416   0.64068414 -0.27712922]\n",
+      " [        nan -1.39914854  1.72745426 -1.88963459  2.07169284 -2.12647624\n",
+      "   2.20575756 -2.21755524  2.23614779]\n",
+      " [        nan  1.40368379  0.65777607  1.31521898  0.33399365  1.0532618\n",
+      "   0.06801398  0.8231939  -0.10688377]\n",
+      " [        nan -1.18809925  1.02356374 -1.13138734  0.83609069 -0.86925624\n",
+      "   0.58200736 -0.58656289  0.35521387]\n",
+      " [        nan  0.02047147 -1.05205916  0.26436363 -0.74314066  0.3175423\n",
+      "  -0.59512717  0.34583472 -0.50896003]\n",
+      " [        nan  1.05522083 -0.18387239  0.65386683 -0.45767038  0.45756418\n",
+      "  -0.50457051  0.39261437 -0.48068484]\n",
+      " [        nan -1.25856864  1.24730351 -1.36047982  1.19040188 -1.21089986\n",
+      "   0.99954288 -0.98284346  0.78641006]\n",
+      " [        nan  1.01652373 -0.26026495  0.60523415 -0.50443221  0.42953253\n",
+      "  -0.52586746  0.38004958 -0.48918321]\n",
+      " [        nan -0.86850148  0.15090895 -0.35856156 -0.20348824  0.00737544\n",
+      "  -0.35988849  0.20336125 -0.40799244]\n",
+      " [        nan  1.08118944 -0.13069368  0.68898157 -0.42265287  0.47933292\n",
+      "  -0.48742104  0.40310485 -0.47332885]\n",
+      " [        nan  0.06079095 -1.06392135  0.26549802 -0.74330578  0.31755739\n",
+      "  -0.59512893  0.34583488 -0.50896005]\n",
+      " [        nan  0.10903438 -1.07324584  0.26609478 -0.74336489  0.31756112\n",
+      "  -0.59512924  0.3458349  -0.50896005]\n",
+      " [        nan -1.189219    1.02703041 -1.13484786  0.84130725 -0.87415795\n",
+      "   0.58784384 -0.59195863  0.36093158]\n",
+      " [        nan -1.49937307  2.09727448 -2.32976191  2.86295131 -3.01346628\n",
+      "   3.46612318 -3.6084978   3.99621819]\n",
+      " [        nan -0.4113663  -0.69265464  0.15667886 -0.6903931   0.30052532\n",
+      "  -0.58789809  0.3433837  -0.50798781]\n",
+      " [        nan  0.28946415 -1.06110073  0.26717821 -0.74327564  0.31756767\n",
+      "  -0.59512869  0.34583494 -0.50896005]\n",
+      " [        nan  0.40617886 -1.01372236  0.27360119 -0.74191841  0.31775144\n",
+      "  -0.59509641  0.34583943 -0.50895932]\n",
+      " [        nan  1.71429403  1.6412879   2.32349885  1.90139203  2.57819936\n",
+      "   1.95547651  2.64403118  1.91405688]\n",
+      " [        nan  0.65737055 -0.8064407   0.33096379 -0.71709288  0.32465294\n",
+      "  -0.5926031   0.34655353 -0.50872084]]\n",
+      "lambda\t\tTrain Error\tValidation Error\n",
+      " 0.000000\t0.029720\tnan\n",
+      " 0.001000\t0.174792\tnan\n",
+      " 0.003000\t0.249938\tnan\n",
+      " 0.010000\t0.385063\tnan\n",
+      " 0.030000\t0.669275\tnan\n",
+      " 0.100000\t1.443470\tnan\n",
+      " 0.300000\t3.101591\tnan\n",
+      " 1.000000\t7.268148\tnan\n",
+      " 3.000000\t15.867688\tnan\n",
+      " 10.000000\t33.372203\tnan\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "lambda_vec, error_train, error_val = validationCurve(X_poly, y, X_poly_val, yval)\n",
-    "\n",
     "pyplot.plot(lambda_vec, error_train, '-o', lambda_vec, error_val, '-o', lw=2)\n",
     "pyplot.legend(['Train', 'Cross Validation'])\n",
     "pyplot.xlabel('lambda')\n",
@@ -850,9 +1148,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 75,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise regularized-linear-regression-and-bias-variance\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "[1.         0.84147098 0.54030231]\n",
+      "[1.         0.93312501 0.72953357]\n"
+     ]
+    },
+    {
+     "ename": "ValueError",
+     "evalue": "operands could not be broadcast together with shapes (10,3) (2,) (10,3) ",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "\u001b[1;32m<ipython-input-75-367afd018817>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mgrader\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m5\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mvalidationCurve\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mgrader\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgrade\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[1;32mD:\\ibshar\\Courses\\Stanford - Machine Learning\\assignments\\ml-coursera-python-assignments\\submission.py\u001b[0m in \u001b[0;36mgrade\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m     28\u001b[0m         \u001b[1;31m# Evaluate the different parts of exercise\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     29\u001b[0m         \u001b[0mparts\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mOrderedDict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 30\u001b[1;33m         \u001b[1;32mfor\u001b[0m \u001b[0mpart_id\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mresult\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     31\u001b[0m             \u001b[0mparts\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpart_id\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m{\u001b[0m\u001b[1;34m'output'\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0msprintf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'%0.5f '\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     32\u001b[0m         \u001b[0mresult\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mresponse\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrequest\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mparts\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32mD:\\ibshar\\Courses\\Stanford - Machine Learning\\assignments\\ml-coursera-python-assignments\\Exercise5\\utils.py\u001b[0m in \u001b[0;36m__iter__\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    156\u001b[0m                     \u001b[0mres\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mX\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m8\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    157\u001b[0m                 \u001b[1;32melif\u001b[0m \u001b[0mpart_id\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;36m5\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 158\u001b[1;33m                     \u001b[0mres\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mhstack\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mX\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mXval\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0myval\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtolist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    159\u001b[0m                 \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    160\u001b[0m                     \u001b[1;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32m<ipython-input-73-a68ac273c45c>\u001b[0m in \u001b[0;36mvalidationCurve\u001b[1;34m(X, y, Xval, yval)\u001b[0m\n\u001b[0;32m     71\u001b[0m     \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     72\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 73\u001b[1;33m     \u001b[0mXval\u001b[0m \u001b[1;33m-=\u001b[0m \u001b[0mmu\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     74\u001b[0m     \u001b[0mXval\u001b[0m \u001b[1;33m/=\u001b[0m \u001b[0msigma\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     75\u001b[0m     \u001b[1;31m# Xval = np.concatenate([np.ones((yval.size, 1)), Xval], axis=1)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;31mValueError\u001b[0m: operands could not be broadcast together with shapes (10,3) (2,) (10,3) "
+     ]
+    }
+   ],
    "source": [
     "grader[5] = validationCurve\n",
     "grader.grade()"
@@ -896,9 +1221,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": []
   }
@@ -919,7 +1242,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.4"
+   "version": "3.7.0"
   }
  },
  "nbformat": 4,
diff --git a/Exercise6/exercise6.ipynb b/Exercise6/exercise6.ipynb
index cdc43975..9ae03929 100755
--- a/Exercise6/exercise6.ipynb
+++ b/Exercise6/exercise6.ipynb
@@ -18,7 +18,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -101,9 +101,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Load from ex6data1\n",
     "# You will have X, y as keys in the dict data\n",
@@ -147,9 +160,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# You should try to change the C value below and see how the decision\n",
     "# boundary varies (e.g., try C = 1000)\n",
@@ -180,7 +206,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -212,7 +238,7 @@
     "    \"\"\"\n",
     "    sim = 0\n",
     "    # ====================== YOUR CODE HERE ======================\n",
-    "\n",
+    "    sim = np.exp(- (np.sum(np.square(np.abs(x2 - x1))) / (2 * (sigma**2))))\n",
     "\n",
     "\n",
     "    # =============================================================\n",
@@ -228,9 +254,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Gaussian Kernel between x1 = [1, 2, 1], x2 = [0, 4, -1], sigma = 2.00:\n",
+      "\t0.324652\n",
+      "(for sigma = 2, this value should be about 0.324652)\n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "x1 = np.array([1, 2, 1])\n",
     "x2 = np.array([0, 4, -1])\n",
@@ -251,9 +288,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise support-vector-machines\n",
+      "\n",
+      "Login (email address): ibrahimsharafelden@gmail.com\n",
+      "Token: wRhcqjekY0A9dPk8\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "                            Gaussian Kernel |  25 /  25 | Nice work!\n",
+      "        Parameters (C, sigma) for Dataset 3 |   0 /  25 | \n",
+      "                           Email Processing |   0 /  25 | \n",
+      "                   Email Feature Extraction |   0 /  25 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  25 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[1] = gaussianKernel\n",
     "grader.grade()"
@@ -272,9 +330,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Load from ex6data2\n",
     "# You will have X, y as keys in the dict data\n",
@@ -298,9 +369,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# SVM Parameters\n",
     "C = 1\n",
@@ -326,9 +410,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Load from ex6data3\n",
     "# You will have X, y, Xval, yval as keys in the dict data\n",
@@ -356,7 +453,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -408,10 +505,18 @@
     "    # You need to return the following variables correctly.\n",
     "    C = 1\n",
     "    sigma = 0.3\n",
+    "    trial_values = [0.01, 0.03, 0.1, 0.3, 1, 3, 10, 30]\n",
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
-    "\n",
-    "    \n",
+    "    error = 100000\n",
+    "    for i in trial_values:\n",
+    "        for j in trial_values:\n",
+    "            model = utils.svmTrain(X, y, i, gaussianKernel, args=(j,))\n",
+    "            predictions = utils.svmPredict(model, Xval)\n",
+    "            new_error = np.mean(predictions != yval)\n",
+    "            if new_error < error:\n",
+    "                error = new_error\n",
+    "                C, sigma = i, j \n",
     "    \n",
     "    # ============================================================\n",
     "    return C, sigma"
@@ -426,9 +531,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 27,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.3 0.1\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Try different SVM Parameters here\n",
     "C, sigma = dataset3Params(X, y, Xval, yval)\n",
@@ -451,9 +576,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 25,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise support-vector-machines\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): \n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "                            Gaussian Kernel |  25 /  25 | Nice work!\n",
+      "        Parameters (C, sigma) for Dataset 3 |  25 /  25 | Nice work!\n",
+      "                           Email Processing |   0 /  25 | \n",
+      "                   Email Feature Extraction |   0 /  25 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  50 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[2] = lambda : (C, sigma)\n",
     "grader.grade()"
@@ -555,7 +700,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -654,9 +799,12 @@
     "\n",
     "        # Look up the word in the dictionary and add to word_indices if found\n",
     "        # ====================== YOUR CODE HERE ======================\n",
-    "\n",
-    "        \n",
-    "\n",
+    "        try:\n",
+    "            idx = vocabList.index(word)\n",
+    "            word_indices.append(idx)\n",
+    "        except ValueError:\n",
+    "            pass\n",
+    "    \n",
     "        # =============================================================\n",
     "\n",
     "    if verbose:\n",
@@ -676,9 +824,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 30,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "----------------\n",
+      "Processed email:\n",
+      "----------------\n",
+      "anyon know how much it cost to host a web portal well it depend on how mani visitor your expect thi can be anywher from less than number buck a month to a coupl of dollar number you should checkout httpaddr or perhap amazon ec number if your run someth big to unsubscrib yourself from thi mail list send an email to emailaddr\n",
+      "-------------\n",
+      "Word Indices:\n",
+      "-------------\n",
+      "[85, 915, 793, 1076, 882, 369, 1698, 789, 1821, 1830, 882, 430, 1170, 793, 1001, 1894, 591, 1675, 237, 161, 88, 687, 944, 1662, 1119, 1061, 1698, 374, 1161, 476, 1119, 1892, 1509, 798, 1181, 1236, 511, 1119, 809, 1894, 1439, 1546, 180, 1698, 1757, 1895, 687, 1675, 991, 960, 1476, 70, 529, 1698, 530]\n"
+     ]
+    }
+   ],
    "source": [
     "#  To use an SVM to classify emails into Spam v.s. Non-Spam, you first need\n",
     "#  to convert each email into a vector of features. In this part, you will\n",
@@ -708,9 +871,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 31,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise support-vector-machines\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "                            Gaussian Kernel |  25 /  25 | Nice work!\n",
+      "        Parameters (C, sigma) for Dataset 3 |  25 /  25 | Nice work!\n",
+      "                           Email Processing |  25 /  25 | Nice work!\n",
+      "                   Email Feature Extraction |   0 /  25 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  75 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[3] = processEmail\n",
     "grader.grade()"
@@ -738,7 +921,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -798,7 +981,8 @@
     "    x = np.zeros(n)\n",
     "\n",
     "    # ===================== YOUR CODE HERE ======================\n",
-    "\n",
+    "    for i in word_indices:\n",
+    "        x[i] = 1\n",
     "    \n",
     "    \n",
     "    # ===========================================================\n",
@@ -815,9 +999,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 37,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "----------------\n",
+      "Processed email:\n",
+      "----------------\n",
+      "anyon know how much it cost to host a web portal well it depend on how mani visitor your expect thi can be anywher from less than number buck a month to a coupl of dollar number you should checkout httpaddr or perhap amazon ec number if your run someth big to unsubscrib yourself from thi mail list send an email to emailaddr\n",
+      "\n",
+      "Length of feature vector: 1899\n",
+      "Number of non-zero entries: 45\n"
+     ]
+    }
+   ],
    "source": [
     "# Extract Features\n",
     "with open(os.path.join('Data', 'emailSample1.txt')) as fid:\n",
@@ -840,9 +1038,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 38,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise support-vector-machines\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "                            Gaussian Kernel |  25 /  25 | Nice work!\n",
+      "        Parameters (C, sigma) for Dataset 3 |  25 /  25 | Nice work!\n",
+      "                           Email Processing |  25 /  25 | Nice work!\n",
+      "                   Email Feature Extraction |  25 /  25 | Nice work!\n",
+      "                                  --------------------------------\n",
+      "                                            | 100 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[4] = emailFeatures\n",
     "grader.grade()"
@@ -862,9 +1080,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 39,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Training Linear SVM (Spam Classification)\n",
+      "This may take 1 to 2 minutes ...\n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "# Load the Spam Email dataset\n",
     "# You will have X, y in your environment\n",
@@ -880,9 +1108,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 40,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Training Accuracy: 99.85\n"
+     ]
+    }
+   ],
    "source": [
     "# Compute the training accuracy\n",
     "p = utils.svmPredict(model, X)\n",
@@ -899,9 +1135,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 41,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Evaluating the trained Linear SVM on a test set ...\n",
+      "Test Accuracy: 98.80\n"
+     ]
+    }
+   ],
    "source": [
     "# Load the test dataset\n",
     "# You will have Xtest, ytest in your environment\n",
@@ -933,9 +1178,34 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 42,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Top predictors of spam:\n",
+      "word            weight         \n",
+      "----            ------\n",
+      "our             0.50\n",
+      "click           0.46\n",
+      "remov           0.42\n",
+      "guarante        0.38\n",
+      "visit           0.38\n",
+      "basenumb        0.34\n",
+      "dollar          0.32\n",
+      "will            0.27\n",
+      "price           0.27\n",
+      "most            0.26\n",
+      "pleas           0.26\n",
+      "lo              0.25\n",
+      "nbsp            0.25\n",
+      "hour            0.24\n",
+      "ga              0.24\n"
+     ]
+    }
+   ],
    "source": [
     "# Sort the weights and obtin the vocabulary list\n",
     "# NOTE some words have the same weights, \n",
@@ -964,9 +1234,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 43,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Processed Data\\emailSample1.txt\n",
+      "Spam Classification: not spam\n"
+     ]
+    }
+   ],
    "source": [
     "filename = os.path.join('Data', 'emailSample1.txt')\n",
     "\n",
@@ -1021,7 +1301,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.4"
+   "version": "3.7.0"
   }
  },
  "nbformat": 4,
diff --git a/Exercise7/exercise7.ipynb b/Exercise7/exercise7.ipynb
index 06681122..02c3088c 100755
--- a/Exercise7/exercise7.ipynb
+++ b/Exercise7/exercise7.ipynb
@@ -18,7 +18,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -142,7 +142,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -185,8 +185,9 @@
     "    idx = np.zeros(X.shape[0], dtype=int)\n",
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
-    "\n",
-    "    \n",
+    "    for i in range(len(idx)):\n",
+    "        distances = np.sum((centroids - X[i])**2, axis=1)\n",
+    "        idx[i] = np.argmin(distances)\n",
     "    \n",
     "    # =============================================================\n",
     "    return idx"
@@ -201,9 +202,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Closest centroids for the first 3 examples:\n",
+      "[0 2 1]\n",
+      "(the closest centroids should be 0, 2, 1 respectively)\n"
+     ]
+    }
+   ],
    "source": [
     "# Load an example dataset that we will be using\n",
     "data = loadmat(os.path.join('Data', 'ex7data2.mat'))\n",
@@ -230,9 +241,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise k-means-clustering-and-pca\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "           Find Closest Centroids (k-Means) |  30 /  30 | Nice work!\n",
+      "           Compute Centroid Means (k-Means) |   0 /  30 | \n",
+      "                                        PCA |   0 /  20 | \n",
+      "                         Project Data (PCA) |   0 /  10 | \n",
+      "                         Recover Data (PCA) |   0 /  10 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  30 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[1] = findClosestCentroids\n",
     "grader.grade()"
@@ -257,7 +289,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -304,8 +336,14 @@
     "\n",
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
-    "\n",
-    "    \n",
+    "    for k in range(K):\n",
+    "        summation = np.zeros(X[0].shape)\n",
+    "        pts_counter = 0\n",
+    "        for i in range(len(idx)):\n",
+    "            if idx[i] == k:\n",
+    "                pts_counter += 1\n",
+    "                summation += X[i]\n",
+    "        centroids[k] = summation / pts_counter\n",
     "    \n",
     "    # =============================================================\n",
     "    return centroids"
@@ -320,9 +358,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Centroids computed after initial finding of closest centroids:\n",
+      "[[2.42830111 3.15792418]\n",
+      " [5.81350331 2.63365645]\n",
+      " [7.11938687 3.6166844 ]]\n",
+      "\n",
+      "The centroids should be\n",
+      "   [ 2.428301 3.157924 ]\n",
+      "   [ 5.813503 2.633656 ]\n",
+      "   [ 7.119387 3.616684 ]\n"
+     ]
+    }
+   ],
    "source": [
     "# Compute means based on the closest centroids found in the previous part.\n",
     "centroids = computeCentroids(X, idx, K)\n",
@@ -344,9 +398,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise k-means-clustering-and-pca\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "           Find Closest Centroids (k-Means) |  30 /  30 | Nice work!\n",
+      "           Compute Centroid Means (k-Means) |  30 /  30 | Nice work!\n",
+      "                                        PCA |   0 /  20 | \n",
+      "                         Project Data (PCA) |   0 /  10 | \n",
+      "                         Recover Data (PCA) |   0 /  10 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  60 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[2] = computeCentroids\n",
     "grader.grade()"
@@ -367,11 +442,4345 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {
     "scrolled": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<link rel=\"stylesheet\"\n",
+       "href=\"https://maxcdn.bootstrapcdn.com/font-awesome/4.4.0//n",
+       "css/font-awesome.min.css\">\n",
+       "<script language=\"javascript\">\n",
+       "  /* Define the Animation class */\n",
+       "  function Animation(frames, img_id, slider_id, interval, loop_select_id){\n",
+       "    this.img_id = img_id;\n",
+       "    this.slider_id = slider_id;\n",
+       "    this.loop_select_id = loop_select_id;\n",
+       "    this.interval = interval;\n",
+       "    this.current_frame = 0;\n",
+       "    this.direction = 0;\n",
+       "    this.timer = null;\n",
+       "    this.frames = new Array(frames.length);\n",
+       "\n",
+       "    for (var i=0; i<frames.length; i++)\n",
+       "    {\n",
+       "     this.frames[i] = new Image();\n",
+       "     this.frames[i].src = frames[i];\n",
+       "    }\n",
+       "    document.getElementById(this.slider_id).max = this.frames.length - 1;\n",
+       "    this.set_frame(this.current_frame);\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.get_loop_state = function(){\n",
+       "    var button_group = document[this.loop_select_id].state;\n",
+       "    for (var i = 0; i < button_group.length; i++) {\n",
+       "        var button = button_group[i];\n",
+       "        if (button.checked) {\n",
+       "            return button.value;\n",
+       "        }\n",
+       "    }\n",
+       "    return undefined;\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.set_frame = function(frame){\n",
+       "    this.current_frame = frame;\n",
+       "    document.getElementById(this.img_id).src =\n",
+       "            this.frames[this.current_frame].src;\n",
+       "    document.getElementById(this.slider_id).value = this.current_frame;\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.next_frame = function()\n",
+       "  {\n",
+       "    this.set_frame(Math.min(this.frames.length - 1, this.current_frame + 1));\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.previous_frame = function()\n",
+       "  {\n",
+       "    this.set_frame(Math.max(0, this.current_frame - 1));\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.first_frame = function()\n",
+       "  {\n",
+       "    this.set_frame(0);\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.last_frame = function()\n",
+       "  {\n",
+       "    this.set_frame(this.frames.length - 1);\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.slower = function()\n",
+       "  {\n",
+       "    this.interval /= 0.7;\n",
+       "    if(this.direction > 0){this.play_animation();}\n",
+       "    else if(this.direction < 0){this.reverse_animation();}\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.faster = function()\n",
+       "  {\n",
+       "    this.interval *= 0.7;\n",
+       "    if(this.direction > 0){this.play_animation();}\n",
+       "    else if(this.direction < 0){this.reverse_animation();}\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.anim_step_forward = function()\n",
+       "  {\n",
+       "    this.current_frame += 1;\n",
+       "    if(this.current_frame < this.frames.length){\n",
+       "      this.set_frame(this.current_frame);\n",
+       "    }else{\n",
+       "      var loop_state = this.get_loop_state();\n",
+       "      if(loop_state == \"loop\"){\n",
+       "        this.first_frame();\n",
+       "      }else if(loop_state == \"reflect\"){\n",
+       "        this.last_frame();\n",
+       "        this.reverse_animation();\n",
+       "      }else{\n",
+       "        this.pause_animation();\n",
+       "        this.last_frame();\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.anim_step_reverse = function()\n",
+       "  {\n",
+       "    this.current_frame -= 1;\n",
+       "    if(this.current_frame >= 0){\n",
+       "      this.set_frame(this.current_frame);\n",
+       "    }else{\n",
+       "      var loop_state = this.get_loop_state();\n",
+       "      if(loop_state == \"loop\"){\n",
+       "        this.last_frame();\n",
+       "      }else if(loop_state == \"reflect\"){\n",
+       "        this.first_frame();\n",
+       "        this.play_animation();\n",
+       "      }else{\n",
+       "        this.pause_animation();\n",
+       "        this.first_frame();\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.pause_animation = function()\n",
+       "  {\n",
+       "    this.direction = 0;\n",
+       "    if (this.timer){\n",
+       "      clearInterval(this.timer);\n",
+       "      this.timer = null;\n",
+       "    }\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.play_animation = function()\n",
+       "  {\n",
+       "    this.pause_animation();\n",
+       "    this.direction = 1;\n",
+       "    var t = this;\n",
+       "    if (!this.timer) this.timer = setInterval(function() {\n",
+       "        t.anim_step_forward();\n",
+       "    }, this.interval);\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.reverse_animation = function()\n",
+       "  {\n",
+       "    this.pause_animation();\n",
+       "    this.direction = -1;\n",
+       "    var t = this;\n",
+       "    if (!this.timer) this.timer = setInterval(function() {\n",
+       "        t.anim_step_reverse();\n",
+       "    }, this.interval);\n",
+       "  }\n",
+       "</script>\n",
+       "\n",
+       "<div class=\"animation\" align=\"center\">\n",
+       "    <img id=\"_anim_img907f215cb3094a888444535ec2884c02\">\n",
+       "    <br>\n",
+       "    <input id=\"_anim_slider907f215cb3094a888444535ec2884c02\" type=\"range\" style=\"width:350px\"\n",
+       "           name=\"points\" min=\"0\" max=\"1\" step=\"1\" value=\"0\"\n",
+       "           onchange=\"anim907f215cb3094a888444535ec2884c02.set_frame(parseInt(this.value));\"></input>\n",
+       "    <br>\n",
+       "    <button onclick=\"anim907f215cb3094a888444535ec2884c02.slower()\"><i class=\"fa fa-minus\"></i></button>\n",
+       "    <button onclick=\"anim907f215cb3094a888444535ec2884c02.first_frame()\"><i class=\"fa fa-fast-backward\">\n",
+       "        </i></button>\n",
+       "    <button onclick=\"anim907f215cb3094a888444535ec2884c02.previous_frame()\">\n",
+       "        <i class=\"fa fa-step-backward\"></i></button>\n",
+       "    <button onclick=\"anim907f215cb3094a888444535ec2884c02.reverse_animation()\">\n",
+       "        <i class=\"fa fa-play fa-flip-horizontal\"></i></button>\n",
+       "    <button onclick=\"anim907f215cb3094a888444535ec2884c02.pause_animation()\"><i class=\"fa fa-pause\">\n",
+       "        </i></button>\n",
+       "    <button onclick=\"anim907f215cb3094a888444535ec2884c02.play_animation()\"><i class=\"fa fa-play\"></i>\n",
+       "        </button>\n",
+       "    <button onclick=\"anim907f215cb3094a888444535ec2884c02.next_frame()\"><i class=\"fa fa-step-forward\">\n",
+       "        </i></button>\n",
+       "    <button onclick=\"anim907f215cb3094a888444535ec2884c02.last_frame()\"><i class=\"fa fa-fast-forward\">\n",
+       "        </i></button>\n",
+       "    <button onclick=\"anim907f215cb3094a888444535ec2884c02.faster()\"><i class=\"fa fa-plus\"></i></button>\n",
+       "  <form action=\"#n\" name=\"_anim_loop_select907f215cb3094a888444535ec2884c02\" class=\"anim_control\">\n",
+       "    <input type=\"radio\" name=\"state\"\n",
+       "           value=\"once\" > Once </input>\n",
+       "    <input type=\"radio\" name=\"state\"\n",
+       "           value=\"loop\" checked> Loop </input>\n",
+       "    <input type=\"radio\" name=\"state\"\n",
+       "           value=\"reflect\" > Reflect </input>\n",
+       "  </form>\n",
+       "</div>\n",
+       "\n",
+       "\n",
+       "<script language=\"javascript\">\n",
+       "  /* Instantiate the Animation class. */\n",
+       "  /* The IDs given should match those used in the template above. */\n",
+       "  (function() {\n",
+       "    var img_id = \"_anim_img907f215cb3094a888444535ec2884c02\";\n",
+       "    var slider_id = \"_anim_slider907f215cb3094a888444535ec2884c02\";\n",
+       "    var loop_select_id = \"_anim_loop_select907f215cb3094a888444535ec2884c02\";\n",
+       "    var frames = new Array(0);\n",
+       "    \n",
+       "  frames[0] = \"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAbAAAAEgCAYAAADVKCZpAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\\\n",
+       "AAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBo\\\n",
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+       "QgihSxLAhBBC6JIEMCGEELokAUwIIYQuSQATQgihSxLAhBBC6JIEMCGEELokAUwIIYQuSQATQgih\\\n",
+       "SxLAhBBC6JIEMCGEELokAUwIIYQuSQATQgihS/8PAyXG2osuQHcAAAAASUVORK5CYII=\\\n",
+       "\"\n",
+       "\n",
+       "\n",
+       "    /* set a timeout to make sure all the above elements are created before\n",
+       "       the object is initialized. */\n",
+       "    setTimeout(function() {\n",
+       "        anim907f215cb3094a888444535ec2884c02 = new Animation(frames, img_id, slider_id, 500.0,\n",
+       "                                 loop_select_id);\n",
+       "    }, 0);\n",
+       "  })()\n",
+       "</script>\n"
+      ],
+      "text/plain": [
+       "<matplotlib.animation.FuncAnimation at 0x75e9e10>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Load an example dataset\n",
     "data = loadmat(os.path.join('Data', 'ex7data2.mat'))\n",
@@ -422,7 +4831,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -453,8 +4862,9 @@
     "    centroids = np.zeros((K, n))\n",
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
-    "\n",
-    "\n",
+    "    randidx = np.random.permutation(X.shape[0])\n",
+    "    # Take the first K examples as centroids\n",
+    "    centroids = X[randidx[:K], :]\n",
     "    \n",
     "    # =============================================================\n",
     "    return centroids"
@@ -503,9 +4913,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# ======= Experiment with these parameters ================\n",
     "# You should try different values for those parameters\n",
@@ -586,9 +5009,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Load the dataset into the variable X \n",
     "data = loadmat(os.path.join('Data', 'ex7data1.mat'))\n",
@@ -627,7 +5063,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -673,8 +5109,8 @@
     "    S = np.zeros(n)\n",
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
-    "\n",
-    "    \n",
+    "    Sigma = (X.T @ X) / m\n",
+    "    U, S, V = np.linalg.svd(Sigma)\n",
     "    \n",
     "    # ============================================================\n",
     "    return U, S"
@@ -699,9 +5135,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Top eigenvector: U[:, 0] = [-0.707107 -0.707107]\n",
+      " (you should expect to see [-0.707107 -0.707107])\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "#  Before running PCA, it is important to first normalize X\n",
     "X_norm, mu, sigma = utils.featureNormalize(X)\n",
@@ -735,9 +5192,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise k-means-clustering-and-pca\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "           Find Closest Centroids (k-Means) |  30 /  30 | Nice work!\n",
+      "           Compute Centroid Means (k-Means) |  30 /  30 | Nice work!\n",
+      "                                        PCA |  20 /  20 | Nice work!\n",
+      "                         Project Data (PCA) |   0 /  10 | \n",
+      "                         Recover Data (PCA) |   0 /  10 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  80 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[3] = pca\n",
     "grader.grade()"
@@ -763,7 +5241,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -807,8 +5285,8 @@
     "    Z = np.zeros((X.shape[0], K))\n",
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
-    "\n",
-    "\n",
+    "    u_reduce = U[:, :K]\n",
+    "    Z = X @ u_reduce\n",
     "    \n",
     "    # =============================================================\n",
     "    return Z"
@@ -823,9 +5301,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Projection of the first example: 1.481274\n",
+      "(this value should be about    : 1.481274)\n"
+     ]
+    }
+   ],
    "source": [
     "#  Project the data onto K = 1 dimension\n",
     "K = 1\n",
@@ -843,9 +5330,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise k-means-clustering-and-pca\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "           Find Closest Centroids (k-Means) |  30 /  30 | Nice work!\n",
+      "           Compute Centroid Means (k-Means) |  30 /  30 | Nice work!\n",
+      "                                        PCA |  20 /  20 | Nice work!\n",
+      "                         Project Data (PCA) |  10 /  10 | Nice work!\n",
+      "                         Recover Data (PCA) |   0 /  10 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  90 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[4] = projectData\n",
     "grader.grade()"
@@ -864,7 +5372,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -912,9 +5420,8 @@
     "    X_rec = np.zeros((Z.shape[0], U.shape[0]))\n",
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
-    "\n",
+    "    X_rec = Z @ U[:, :K].T\n",
     "    \n",
-    "\n",
     "    # =============================================================\n",
     "    return X_rec"
    ]
@@ -932,9 +5439,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Approximation of the first example: [-1.047419 -1.047419]\n",
+      "       (this value should be about  [-1.047419 -1.047419])\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 360x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "X_rec  = recoverData(Z, U, K)\n",
     "print('Approximation of the first example: [{:.6f} {:.6f}]'.format(X_rec[0, 0], X_rec[0, 1]))\n",
@@ -962,9 +5490,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise k-means-clustering-and-pca\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "           Find Closest Centroids (k-Means) |  30 /  30 | Nice work!\n",
+      "           Compute Centroid Means (k-Means) |  30 /  30 | Nice work!\n",
+      "                                        PCA |  20 /  20 | Nice work!\n",
+      "                         Project Data (PCA) |  10 /  10 | Nice work!\n",
+      "                         Recover Data (PCA) |  10 /  10 | Nice work!\n",
+      "                                  --------------------------------\n",
+      "                                            | 100 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[5] = recoverData\n",
     "grader.grade()"
@@ -985,9 +5534,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x576 with 100 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "#  Load Face dataset\n",
     "data = loadmat(os.path.join('Data', 'ex7faces.mat'))\n",
@@ -1010,9 +5572,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x576 with 36 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "#  normalize X by subtracting the mean value from each feature\n",
     "X_norm, mu, sigma = utils.featureNormalize(X)\n",
@@ -1037,9 +5612,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The projected data Z has a shape of:  (5000, 100)\n"
+     ]
+    }
+   ],
    "source": [
     "#  Project images to the eigen space using the top k eigenvectors \n",
     "#  If you are applying a machine learning algorithm \n",
@@ -1068,9 +5651,34 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 24,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x432 with 100 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x432 with 100 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "#  Project images to the eigen space using the top K eigen vectors and \n",
     "#  visualize only using those K dimensions\n",
@@ -1092,6 +5700,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "\n",
     "### 2.5 Optional (ungraded) exercise: PCA for visualization\n",
     "\n",
     "In the earlier K-means image compression exercise, you used the K-means algorithm in the 3-dimensional RGB space. We reduced each pixel of the RGB image to be represented by 16 clusters. In the next cell, we have provided code to visualize the final pixel assignments in this 3D space. Each data point is colored according to the cluster it has been assigned to. You can drag your mouse on the figure to rotate and inspect this data in 3 dimensions."
@@ -1099,9 +5708,802 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 28,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "/* Put everything inside the global mpl namespace */\n",
+       "window.mpl = {};\n",
+       "\n",
+       "\n",
+       "mpl.get_websocket_type = function() {\n",
+       "    if (typeof(WebSocket) !== 'undefined') {\n",
+       "        return WebSocket;\n",
+       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+       "        return MozWebSocket;\n",
+       "    } else {\n",
+       "        alert('Your browser does not have WebSocket support.' +\n",
+       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+       "              'Firefox 4 and 5 are also supported but you ' +\n",
+       "              'have to enable WebSockets in about:config.');\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+       "    this.id = figure_id;\n",
+       "\n",
+       "    this.ws = websocket;\n",
+       "\n",
+       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
+       "\n",
+       "    if (!this.supports_binary) {\n",
+       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
+       "        if (warnings) {\n",
+       "            warnings.style.display = 'block';\n",
+       "            warnings.textContent = (\n",
+       "                \"This browser does not support binary websocket messages. \" +\n",
+       "                    \"Performance may be slow.\");\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.imageObj = new Image();\n",
+       "\n",
+       "    this.context = undefined;\n",
+       "    this.message = undefined;\n",
+       "    this.canvas = undefined;\n",
+       "    this.rubberband_canvas = undefined;\n",
+       "    this.rubberband_context = undefined;\n",
+       "    this.format_dropdown = undefined;\n",
+       "\n",
+       "    this.image_mode = 'full';\n",
+       "\n",
+       "    this.root = $('<div/>');\n",
+       "    this._root_extra_style(this.root)\n",
+       "    this.root.attr('style', 'display: inline-block');\n",
+       "\n",
+       "    $(parent_element).append(this.root);\n",
+       "\n",
+       "    this._init_header(this);\n",
+       "    this._init_canvas(this);\n",
+       "    this._init_toolbar(this);\n",
+       "\n",
+       "    var fig = this;\n",
+       "\n",
+       "    this.waiting = false;\n",
+       "\n",
+       "    this.ws.onopen =  function () {\n",
+       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+       "            fig.send_message(\"send_image_mode\", {});\n",
+       "            if (mpl.ratio != 1) {\n",
+       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
+       "            }\n",
+       "            fig.send_message(\"refresh\", {});\n",
+       "        }\n",
+       "\n",
+       "    this.imageObj.onload = function() {\n",
+       "            if (fig.image_mode == 'full') {\n",
+       "                // Full images could contain transparency (where diff images\n",
+       "                // almost always do), so we need to clear the canvas so that\n",
+       "                // there is no ghosting.\n",
+       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "            }\n",
+       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
+       "        };\n",
+       "\n",
+       "    this.imageObj.onunload = function() {\n",
+       "        fig.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var backingStore = this.context.backingStorePixelRatio ||\n",
+       "\tthis.context.webkitBackingStorePixelRatio ||\n",
+       "\tthis.context.mozBackingStorePixelRatio ||\n",
+       "\tthis.context.msBackingStorePixelRatio ||\n",
+       "\tthis.context.oBackingStorePixelRatio ||\n",
+       "\tthis.context.backingStorePixelRatio || 1;\n",
+       "\n",
+       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width * mpl.ratio);\n",
+       "        canvas.attr('height', height * mpl.ratio);\n",
+       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'] / mpl.ratio;\n",
+       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+       "    var x1 = msg['x1'] / mpl.ratio;\n",
+       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x * mpl.ratio;\n",
+       "    var y = canvas_pos.y * mpl.ratio;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+       "\n",
+       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
+       "    // object with the appropriate methods. Currently this is a non binary\n",
+       "    // socket, so there is still some room for performance tuning.\n",
+       "    var ws = {};\n",
+       "\n",
+       "    ws.close = function() {\n",
+       "        comm.close()\n",
+       "    };\n",
+       "    ws.send = function(m) {\n",
+       "        //console.log('sending', m);\n",
+       "        comm.send(m);\n",
+       "    };\n",
+       "    // Register the callback with on_msg.\n",
+       "    comm.on_msg(function(msg) {\n",
+       "        //console.log('receiving', msg['content']['data'], msg);\n",
+       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+       "        ws.onmessage(msg['content']['data'])\n",
+       "    });\n",
+       "    return ws;\n",
+       "}\n",
+       "\n",
+       "mpl.mpl_figure_comm = function(comm, msg) {\n",
+       "    // This is the function which gets called when the mpl process\n",
+       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+       "\n",
+       "    var id = msg.content.data.id;\n",
+       "    // Get hold of the div created by the display call when the Comm\n",
+       "    // socket was opened in Python.\n",
+       "    var element = $(\"#\" + id);\n",
+       "    var ws_proxy = comm_websocket_adapter(comm)\n",
+       "\n",
+       "    function ondownload(figure, format) {\n",
+       "        window.open(figure.imageObj.src);\n",
+       "    }\n",
+       "\n",
+       "    var fig = new mpl.figure(id, ws_proxy,\n",
+       "                           ondownload,\n",
+       "                           element.get(0));\n",
+       "\n",
+       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+       "    // web socket which is closed, not our websocket->open comm proxy.\n",
+       "    ws_proxy.onopen();\n",
+       "\n",
+       "    fig.parent_element = element.get(0);\n",
+       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+       "    if (!fig.cell_info) {\n",
+       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
+       "        return;\n",
+       "    }\n",
+       "\n",
+       "    var output_index = fig.cell_info[2]\n",
+       "    var cell = fig.cell_info[0];\n",
+       "\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+       "    var width = fig.canvas.width/mpl.ratio\n",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var width = this.canvas.width/mpl.ratio\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        event.shiftKey = false;\n",
+       "        // Send a \"J\" for go to next cell\n",
+       "        event.which = 74;\n",
+       "        event.keyCode = 74;\n",
+       "        manager.command_mode();\n",
+       "        manager.handle_keydown(event);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img 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\" width=\"432\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# this allows to have interactive plot to rotate the 3-D plot\n",
     "# The double identical statement is on purpose\n",
@@ -1146,9 +6548,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 29,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Subtract the mean to use PCA\n",
     "X_norm, mu, sigma = utils.featureNormalize(X)\n",
@@ -1168,6 +6583,13 @@
     "ax.grid(False)\n",
     "pass"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -1186,7 +6608,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.4"
+   "version": "3.7.0"
   }
  },
  "nbformat": 4,
diff --git a/Exercise8/exercise8.ipynb b/Exercise8/exercise8.ipynb
old mode 100755
new mode 100644
index 3e4aa604..5bc23ec5
--- a/Exercise8/exercise8.ipynb
+++ b/Exercise8/exercise8.ipynb
@@ -23,7 +23,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -97,9 +97,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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HcDXJL/131HTwSUmh1tcmL04KrWemqqbZr+dsm+xqYnLV0+WQGCTF2rVrpyS0devWuTKqLYmFJIVaOpr/BDgrIn4nIi4Gzgb+rIb9ppC0terpm4HyQo5jy99MHct79+7NO5bb29tnHbNffQOcZvSc5zyHW265heOOO47Dhw+zbt06CoUCTz75pPsPrGnVkhQeBsarno8D/zXXTpI+A/wb0CHpYUnvBP5a0n2S7iW5ped7FhCzHUOq695k5a+Bpq9rBHDo0CHe8pa38PTTT7NlyxYeeOAByuVyXga6VCo1OkSzKWqZvPZd4MuSbiS5/H0j8BVJ7wWIiI9Ot1NEXDTN6isXGqi1llqLnGX3SdiyZQuPPPIIHR0dRERTz0/IbuOZxVwsFtm5c2d+TkNDQy6CZ02rliuFB4B/JkkIkAxHPQisTxezeZvupjjT/YLu7e1l586d3HPPPezcuZO9e/dy/fXXs2XLFoAJVw/NYuPGjQwMDOQxX3vttRPmWszVLGbWUPPthGjE4o7m1lQsFqNcLufPy+VyTVVDq0culcvl/B7MzbBkHcrZqCqzRqIeHc2Stku6QtLnJf3fbDnKXGTHuMHBQUqlEhdeeGE+Ie3CCy+kVCoxODg4635Zc8zQ0BA333wzlUqF7du309/fz9q1a5fwLKY6fPgw7e3t7jOwZauWPoUS8PfAPwKH6xuOHSuKxSK7du2aV1G46Yrm7dmzB4C3v/3trF+/nkOHDiEpG/Zcd1n/QX9/f1564z3veQ/r1693E5EtT3NdSgD75nv5sdiLm49a0+T5B4VCYdYml+q5DZs3b54wtyGb8JZNdKte1qxZs+jNRJs2bQpIbu6T3RfBE9Cs2bCYzUeSNknaBNws6X9K2pqtS9ebLan29nbe+ta3Asn9jcfGxti8eTMRwfve9z76+vp45JFHOP3001m9enW+31NPPbVoMbS1tVEulzlw4ACdnZ088MADrF+/Po/PVwe27M2ULUhuvfkgE2/FmS0Pzjf7HM3iK4XWM9OM5rk6aMvl8oTZwVk9oWy/bAZ0uVyeUmtox44d874iWLVq1YTnGzdunDLj2qxZUa/aR41enBRaz0Luu1u9TfUXfltbW/T390/Ytr+/f8oX/Iknnph/sa9cuXLOhFC9TfX7bd++3SOLbFmoS1IAfmOa5ZeA9vm+2UIXJ4XWNN/77maJBKave5TtO11CqE4M2ZVELYkhSwLlcjk6OjqmvJdZM1tIUqhl9NE7gVcCQ+nzc4F/B7ZL+mBE7KnhGGZTTG5/n6tNvre3l4MHD/I3f/M3PPPMMxNGGR133HGce+65ANx77735Phs2bGDFihU89lhya48TTzyR9vZ2SqUSzz77LFu2bEESBw8enPY9u7q6uP3222lvb2fv3r3s3r3bI4uspdWSFI4AL46IUQBJJwGXAz8H7AWcFGzJbN26lWeeeYa2tjYOH05GSLe1tfH0009zxx138JKXvISbbrqJM844g3K5zOOPPw4kyeHHP/4x3/jGN/J5EAMDA7zjHe8A4LTTTuPQoUOsW7eONWvWMDY2xvr16/OEAEnSuuSSSxpw1mZLp5YyF6dmCSFVAbZHxGPAj+sTltn0ent7GRgYYMOGDfm6DRs2MDAwMOHX+zXXXDOhBMYPf/hDDh06RGdnJ+Pj4/T19eVzHHbv3s2hQ4cA6O/vz0tujI+PewKaHXOUXX7PuIG0C9hGMokN4DdJKqf+CfAvEdFT1wiB7u7uGB4ervfb2DKQFdIbGRmZUEivs7MzL6RXvU11E1NbWxv33HMPhUJh2mN0dHTkpbsrlYqL1tmyJ2lfRHTPZ59arhR6SW6wcyZwFvBJoDciDi1FQjCrVkshvWybjo4ONm36yZSaw4cPc/PNNy/KvRzMWtWcfQppD/Zn08WsobIv6mKxOGMp6t7eXsbHx7nqqqt49NFHKRQKHDlyhEcffZQ9e/bk/QhmNlUtBfHGJT2RLj+SdFjSE0sRnNl0ent75yxFvX79eu6///78iiK7uhgZGWH37t0T7uWQXTH4bmhmtV0pTLhngqQ3AS+vW0Rmi2C2KwogTxJZYb2sj8H9CHasm7OjedqdpH+PiFfUIZ5puaPZFltWgjtLGO5Ytla0kI7mWkYf/UbV0xVAN/CLEfHK+Ye4ME4KZmbzt5CkUMvktfOrHj8LPERyn2YzM2sxtfQpvH0pAjEzs8arZfTRKZJukFSRNCrpOkmnLEVwZma2tGqZvHYVcBPwPOBk4OZ0nZmZtZhakkIhIq6KiGfT5RNAoc5xmdkSGBwcnDA3o1Kp5AUD7dhUS1L4vqTfltSWLr8NPFrvwMysvgYHB+nr68sn7WU1o/r6+pwYjmG1JIV3ABcCjwAHgQvSdWa2jBWLxXyWd1dXF11dXfmkvmKx2OjwrEFmHX0kqQ34zYh4wxLFY2ZLJCsM2NXVxdjYGACFQiGvNmvHplmvFCLiMAuckyBpdzpiqVy1bpOk2yR9K/27cSHHNjOz+qil+ehLknZKerWkl2VLDft9AnjdpHWXALdHxAuB29PnZtYAWR+CCwNatVqSwquAlwAfBP42XT4y104RsRd4bNLqNwJXp4+vBt5Uc6RmtqhquTeFHXtqmdG8mDfSOSkiDqbHPShpxoZLSTuAHQDbtm1bxBDMDGq7N4Ude2opiHccyS04T6UqiUTEB+c8uHQqyS07u9Lnj0fEhqrXfxARc/YruCCeLZSrodqxrF4F8W4EfgjsA55eSGBVRiVtTa8StgJuuLS6ycbh79q1a8p9EwAnBrNp1JIUTomIyR3GC3UTcDHw4fTvjYt0XLMpisUiu3btysfhA4yNjXkcvtksaulo/n+SzpjvgSV9Bvg3oEPSw5LeSZIMzpP0LeC89LlZXWTj8LNRNdkoG4/DN5vZjFcK6fyCI+k2b5f0IEnzkYCIiJ+Z7cARcdEML/3SAmM1M7M6m6356GTgzKUKxGyxTR6HD+Tj8H21YDa92ZqPvhMR/zHTsmQRmi2Qx+Gbzd9sVwrtkt4704sR8dE6xGO2aDwO32z+ZpynIOkgcDlJH8IUEfGBOsY1gecpmJnN32LPUzhYywQ1MzNrHbP1KUx7hWBmZq1rtqTgoaNmZseYGZNCREyucGpmZi2ulhnNZmZ2jHBSMDOznJOCmZnlnBTMzCznpGBmZjknBTMzyzkpmJlZzknBzMxyTgpmZpZzUjAzs5yTgpmZ5ZwUzMws56RgZmY5JwUzM8s5KZiZWc5JwczMck4KZmaWc1IwM7Ock4KZmeVWNuJNJT0EjAOHgWcjorsRcZiZ2UQNSQqpnoj4fgPf38zMJnHzkZmZ5RqVFAL4vKR9knY0KAYzM5ukUc1H50TE9yS1A7dJ+kZE7K3eIE0WOwC2bdvWiBjNzI45DblSiIjvpX8rwA3Ay6fZ5oqI6I6I7kKhsNQhmpkdk5Y8KUhaK2l99hj4ZaC81HGYWf0NDg5SqVTy55VKhcHBwQZGZHNpRPPRScANkrL3/3RE/GsD4jCzOhocHKSvr49du3YxNDQEQE9PDyMjIwD09vY2MjybgSKi0THMqbu7O4aHhxsdhpnNQ6VSyZNA1gQ8NjZGZ2cnQ0NDtLe3NzjC1idp33zngXlIqpnVRXt7O0NDQxQKBcbGxhgbG6NQKDghNDknBTMzyzkpmFldZM1H2RVCdsXQ09MzofPZmouTgpnVRalUYmRkhM7OTsrlMuVymc7OTkZGRiiVSo0Oz2bQyNpHZtbCstFFxWIx70MYGhqiVCp55FET8+gjM7MW5dFHZmZ2VJwUzMws56RgZmY5JwUzM8s5KZiZWc5JwczMck4KZmaWc1IwM7Ock4KZmeWcFMzMLOekYGZmOScFMzPLOSmYmVnOScHMzHJOCmZmlnNSMDOznJOCmZnlnBTMzCznpGBmZjknBTMzyzkpmJlZzknBzMxyDUkKkl4n6ZuSvi3pkkbEYGZmUy15UpDUBgwCvwp0AhdJ6lzqOMzMbKpGXCm8HPh2RDwYEc8A1wBvbEAcZmY2ycoGvOfJwH9VPX8Y+LnJG0naAexInz4tqbwEsTXKicD3Gx1EHbXy+bXyuYHPb7nrmO8OjUgKmmZdTFkRcQVwBYCk4YjorndgjeLzW75a+dzA57fcSRqe7z6NaD56GHh+1fNTgO81IA4zM5ukEUnhq8ALJb1A0mrgt4CbGhCHmZlNsuTNRxHxrKQ+4FagDdgdEfvn2O2K+kfWUD6/5auVzw18fsvdvM9PEVOa883M7BjlGc1mZpZzUjAzs1xTJ4VWL4ch6SFJ90n6+kKGjjUbSbslVarnlEjaJOk2Sd9K/25sZIxHY4bzu1TSd9PP8OuSXt/IGI+GpOdLGpJ0QNJ+Se9K1y/7z3CWc2uJz0/S8ZK+Iume9Pw+kK5/gaQvp5/dP6WDe2Y/VrP2KaTlMO4HziMZxvpV4KKIGGloYItI0kNAd0S0xOQZSb8APAl8MiK60nV/DTwWER9OE/vGiPizRsa5UDOc36XAkxHxkUbGthgkbQW2RsTdktYD+4A3Ab/DMv8MZzm3C2mBz0+SgLUR8aSkVcBdwLuA9wLXR8Q1kv4euCciLp/tWM18peByGMtMROwFHpu0+o3A1enjq0n+IS5LM5xfy4iIgxFxd/p4HDhAUoFg2X+Gs5xbS4jEk+nTVekSwGuAz6bra/rsmjkpTFcOo2U+xFQAn5e0Ly3r0YpOioiDkPzDBNobHE899Em6N21eWnZNK9ORdCpwFvBlWuwznHRu0CKfn6Q2SV8HKsBtwAPA4xHxbLpJTd+hzZwUaiqHscydExEvI6kY25s2T9jycjlwOnAmcBD428aGc/QkrQOuA94dEU80Op7FNM25tcznFxGHI+JMkioRLwdePN1mcx2nmZNCy5fDiIjvpX8rwA0kH2SrGU3bc7N23UqD41lUETGa/mM8AvwDy/wzTNujrwM+FRHXp6tb4jOc7txa7fMDiIjHgTuAVwAbJGWTlGv6Dm3mpNDS5TAkrU07vJC0FvhloBUrwd4EXJw+vhi4sYGxLLrsyzL1ZpbxZ5h2Vl4JHIiIj1a9tOw/w5nOrVU+P0kFSRvSx2uA15L0mwwBF6Sb1fTZNe3oI4B0eNjH+Ek5jA81OKRFI+k0kqsDSMqNfHq5n5+kzwDnkpQjHgX+Avhn4FpgG/CfQDEilmVn7Qzndy5J00MADwG/n7W/LzeSfh74InAfcCRd/X6Stvdl/RnOcm4X0QKfn6SfIelIbiP5sX9tRHww/Z65BtgEfA347Yh4etZjNXNSMDOzpdXMzUdmZrbEnBTMzCznpGBmZjknBTMzyzkpmJlZzknBlj1JT869Vb7tuZJeVc945nj/d0t62yIc5xpJL1yMmMyqOSnYseZcoCFJIZ1Z+g7g04twuMuBP12E45hN4KRgLUnS+Wkd+a9J+oKkk9JCaH8AvCetnf/qdCbodZK+mi7npPtfmhZIu0PSg5L+qOrYb0sLqN0jaY+k9ZK+k5ZRQNIJSu6VsWpSWK8B7s4KlKXHvkzS3rTO/89Kuj6tff+X6TZrJX0ufa+ypLekx/oi8NqqEgZmi8L/Q1mrugt4RUSEpN8F/jQi/jitKZ/Xz5f0aeCyiLhL0jbgVn5SSOxFQA+wHvimpMuB7UA/STHD70vaFBHjku4Afo1kBvdvAddFxI8nxXQOSR3/as9ExC8ouenLjcDZJOW5H5B0GcmVzfci4tfSeJ8LEBFHJH0beOk0xzRbMCcFa1WnAP+U1rZZDXxnhu1eC3QmpXEAOCGrSQV8Li0J8LSkCnASaX367MZIVeUe/pGkOeefgbcDvzfNe20lqUdTLavndR+wPyuxIOlBkoKQ9wEfkfRXwL9ExBer9q0Az8NJwRaRm4+sVf0dsDMizgB+Hzh+hu1WAK+MiDPT5eT0JiwA1TViDpP8iBLTlB+OiC8Bp0r6RaAtIqYrrPbUNHFk73Fk0vsdAVZGxP0kVw/3AQOS/rxqm+PTY5otGicFa1XPBb6bPr64av04SXNQ5vNAX/ZE0plzHPd24EJJm9PtN1W99kngM8BVM+x7APjpOSOvIul5wH9HxP8GPgK8rOrl7cD++RzPbC5OCtYKniPp4arlvcClQEnSF4Hqe2DfDLw562gG/gjoTjsAtBtAAAAAnklEQVSOR0g6omcUEfuBDwF3SroHqC4x/SlgI0limM7/AeZ7I6UzgK+kd9TqB7IO6JOAp5ZjRU9rbq6SarZIJF0AvDEi3jrLNjeQdHp/6yjf6z3AExFx5dEcx2wydzSbLQJJf0dyW9XXz7HpJSQdzkeVFIDHgT1HeQyzKXylYGZmOfcpmJlZzknBzMxyTgpmZpZzUjAzs5yTgpmZ5f4/Nkx4Sm+2RDIAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "#  The following command loads the dataset.\n",
     "data = loadmat(os.path.join('Data', 'ex8data1.mat'))\n",
@@ -144,7 +157,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -183,8 +196,8 @@
     "    sigma2 = np.zeros(n)\n",
     "\n",
     "    # ====================== YOUR CODE HERE ======================\n",
-    "\n",
-    "    \n",
+    "    mu = np.sum(X, axis=0) / m\n",
+    "    sigma2 = np.sum(np.square(X - mu), axis=0) / m\n",
     "    # =============================================================\n",
     "    return mu, sigma2"
    ]
@@ -205,9 +218,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 31,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "#  Estimate my and sigma2\n",
     "mu, sigma2 = estimateGaussian(X)\n",
@@ -232,9 +258,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 32,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise anomaly-detection-and-recommender-systems\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "               Estimate Gaussian Parameters |  15 /  15 | Nice work!\n",
+      "                           Select Threshold |   0 /  15 | \n",
+      "               Collaborative Filtering Cost |   0 /  20 | \n",
+      "           Collaborative Filtering Gradient |   0 /  30 | \n",
+      "                           Regularized Cost |   0 /  10 | \n",
+      "                       Regularized Gradient |   0 /  10 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  15 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[1] = estimateGaussian\n",
     "grader.grade()"
@@ -286,7 +334,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -327,13 +375,17 @@
     "    bestEpsilon = 0\n",
     "    bestF1 = 0\n",
     "    F1 = 0\n",
-    "   \n",
+    "\n",
     "    for epsilon in np.linspace(1.01*min(pval), max(pval), 1000):\n",
     "        # ====================== YOUR CODE HERE =======================\n",
-    "\n",
-    "        \n",
+    "        predictions = pval < epsilon\n",
+    "        tp = np.sum((predictions == 1) & (yval == 1))\n",
+    "        fp = np.sum((predictions == 1) & (yval == 0))\n",
+    "        fn = np.sum((predictions == 0) & (yval == 1))\n",
+    "        precision = tp / (tp + fp)\n",
+    "        recall = tp / (tp + fn)\n",
+    "        F1 = (2 * precision * recall) / (precision + recall)\n",
     "        \n",
-    "\n",
     "        # =============================================================\n",
     "        if F1 > bestF1:\n",
     "            bestF1 = F1\n",
@@ -351,9 +403,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 46,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Best epsilon found using cross-validation: 9.00e-05\n",
+      "Best F1 on Cross Validation Set:  0.875000\n",
+      "   (you should see a value epsilon of about 8.99e-05)\n",
+      "   (you should see a Best F1 value of  0.875000)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "pval = utils.multivariateGaussian(Xval, mu, sigma2)\n",
     "\n",
@@ -386,9 +461,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 47,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise anomaly-detection-and-recommender-systems\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "               Estimate Gaussian Parameters |  15 /  15 | Nice work!\n",
+      "                           Select Threshold |  15 /  15 | Nice work!\n",
+      "               Collaborative Filtering Cost |   0 /  20 | \n",
+      "           Collaborative Filtering Gradient |   0 /  30 | \n",
+      "                           Regularized Cost |   0 /  10 | \n",
+      "                       Regularized Gradient |   0 /  10 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  30 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[2] = selectThreshold\n",
     "grader.grade()"
@@ -405,9 +502,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 48,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Best epsilon found using cross-validation: 1.38e-18\n",
+      "Best F1 on Cross Validation Set          : 0.615385\n",
+      "\n",
+      "  (you should see a value epsilon of about 1.38e-18)\n",
+      "   (you should see a Best F1 value of      0.615385)\n",
+      "\n",
+      "# Outliers found: 117\n"
+     ]
+    }
+   ],
    "source": [
     "#  Loads the second dataset. You should now have the\n",
     "#  variables X, Xval, yval in your environment\n",
@@ -453,9 +564,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Average rating for movie 1 (Toy Story): 4.520679 / 5\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Load data\n",
     "data = loadmat(os.path.join('Data', 'ex8_movies.mat'))\n",
@@ -532,7 +663,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -609,10 +740,12 @@
     "    J = 0\n",
     "    X_grad = np.zeros(X.shape)\n",
     "    Theta_grad = np.zeros(Theta.shape)\n",
-    "\n",
+    "    \n",
     "    # ====================== YOUR CODE HERE ======================\n",
-    "\n",
+    "    J = 1/2 * np.sum(np.square(((X @ Theta.T) - Y)) * R) + (lambda_/2 * np.sum(np.square(Theta))) + (lambda_/2 * np.sum(np.square(X)))\n",
     "    \n",
+    "    X_grad = (R * X.dot(Theta.T) - Y).dot(Theta) + (lambda_ * X)\n",
+    "    Theta_grad = (R * X.dot(Theta.T) - Y).T.dot(X) + (lambda_ * Theta)\n",
     "    \n",
     "    # =============================================================\n",
     "    \n",
@@ -629,9 +762,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cost at loaded parameters:  22.22 \n",
+      "(this value should be about 22.22)\n"
+     ]
+    }
+   ],
    "source": [
     "#  Load pre-trained weights (X, Theta, num_users, num_movies, num_features)\n",
     "data = loadmat(os.path.join('Data', 'ex8_movieParams.mat'))\n",
@@ -664,9 +806,37 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 9,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise anomaly-detection-and-recommender-systems\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "(3, 5)\n",
+      "(4, 5)\n",
+      "(4, 3)\n",
+      "(4, 3)\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "               Estimate Gaussian Parameters |   0 /  15 | \n",
+      "                           Select Threshold |   0 /  15 | \n",
+      "               Collaborative Filtering Cost |  20 /  20 | Nice work!\n",
+      "           Collaborative Filtering Gradient |   0 /  30 | \n",
+      "                           Regularized Cost |   0 /  10 | \n",
+      "                       Regularized Gradient |   0 /  10 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  20 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[3] = cofiCostFunc\n",
     "grader.grade()"
@@ -725,9 +895,268 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 27,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "(5, 3)\n",
+      "(4, 3)\n",
+      "(4, 5)\n",
+      "(4, 5)\n",
+      "[[-5.50886187e+00 -5.50886187e+00]\n",
+      " [-1.52166639e+01 -1.52166639e+01]\n",
+      " [-5.62940200e+00 -5.62940200e+00]\n",
+      " [ 3.50825316e-01  3.50825316e-01]\n",
+      " [-2.26781315e-01 -2.26781315e-01]\n",
+      " [-1.10384513e-02 -1.10384513e-02]\n",
+      " [ 4.15968245e+00  4.15968245e+00]\n",
+      " [ 3.81060442e+00  3.81060442e+00]\n",
+      " [ 3.76499923e-01  3.76499923e-01]\n",
+      " [-4.59044233e+00 -4.59044233e+00]\n",
+      " [-4.86548504e+00 -4.86548504e+00]\n",
+      " [ 5.96949970e-01  5.96949970e-01]\n",
+      " [-8.92851582e+00 -8.92851582e+00]\n",
+      " [-6.45050548e+00 -6.45050548e+00]\n",
+      " [-2.76162205e+00 -2.76162205e+00]\n",
+      " [ 2.51178442e+00  2.51178442e+00]\n",
+      " [-3.54185686e-01 -3.54185686e-01]\n",
+      " [-1.64390174e-01 -1.64390174e-01]\n",
+      " [ 5.61734255e-02  5.61734255e-02]\n",
+      " [-9.21678000e-02 -9.21678000e-02]\n",
+      " [ 3.91344930e-01  3.91344930e-01]\n",
+      " [ 2.48805291e+00  2.48805291e+00]\n",
+      " [-7.11975404e-02 -7.11975404e-02]\n",
+      " [-3.78701733e-01 -3.78701733e-01]\n",
+      " [ 1.11608351e-01  1.11608351e-01]\n",
+      " [ 8.72285351e-01  8.72285351e-01]\n",
+      " [-6.92798953e-01 -6.92798953e-01]]\n",
+      "\n",
+      "The above two columns you get should be very similar.(Left-Your Numerical Gradient, Right-Analytical Gradient)\n",
+      "If your cost function implementation is correct, then the relative difference will be small (less than 1e-9).\n",
+      "\n",
+      "Relative Difference: 1.48023e-12\n"
+     ]
+    }
+   ],
    "source": [
     "#  Check gradients by running checkcostFunction\n",
     "utils.checkCostFunction(cofiCostFunc)"
@@ -742,9 +1171,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise anomaly-detection-and-recommender-systems\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "(3, 5)\n",
+      "(4, 5)\n",
+      "(4, 3)\n",
+      "(4, 3)\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "               Estimate Gaussian Parameters |   0 /  15 | \n",
+      "                           Select Threshold |   0 /  15 | \n",
+      "               Collaborative Filtering Cost |  20 /  20 | Nice work!\n",
+      "           Collaborative Filtering Gradient |  30 /  30 | Nice work!\n",
+      "                           Regularized Cost |   0 /  10 | \n",
+      "                       Regularized Gradient |   0 /  10 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  50 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[4] = cofiCostFunc\n",
     "grader.grade()"
@@ -769,9 +1224,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 30,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cost at loaded parameters (lambda = 1.5): 31.34\n",
+      "              (this value should be about 31.34)\n"
+     ]
+    }
+   ],
    "source": [
     "#  Evaluate cost function\n",
     "J, _ = cofiCostFunc(np.concatenate([X.ravel(), Theta.ravel()]),\n",
@@ -790,9 +1254,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 31,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise anomaly-detection-and-recommender-systems\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "(3, 5)\n",
+      "(4, 5)\n",
+      "(4, 3)\n",
+      "(4, 3)\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "               Estimate Gaussian Parameters |   0 /  15 | \n",
+      "                           Select Threshold |   0 /  15 | \n",
+      "               Collaborative Filtering Cost |  20 /  20 | Nice work!\n",
+      "           Collaborative Filtering Gradient |  30 /  30 | Nice work!\n",
+      "                           Regularized Cost |  10 /  10 | Nice work!\n",
+      "                       Regularized Gradient |   0 /  10 | \n",
+      "                                  --------------------------------\n",
+      "                                            |  60 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[5] = cofiCostFunc\n",
     "grader.grade()"
@@ -822,9 +1312,48 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 33,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[  3.40053647   3.40053647]\n",
+      " [  3.53219353   3.53219353]\n",
+      " [ -2.71292049  -2.71292049]\n",
+      " [-15.4064392  -15.4064392 ]\n",
+      " [  0.02687403   0.02687403]\n",
+      " [ -2.12528177  -2.12528177]\n",
+      " [ -0.89588181  -0.89588181]\n",
+      " [  3.46072174   3.46072174]\n",
+      " [  1.01274653   1.01274653]\n",
+      " [ -0.61310966  -0.61310966]\n",
+      " [  1.98500729   1.98500729]\n",
+      " [ -0.46287243  -0.46287243]\n",
+      " [-10.21787434 -10.21787434]\n",
+      " [ -2.36093879  -2.36093879]\n",
+      " [ -2.88192804  -2.88192804]\n",
+      " [  2.85588292   2.85588292]\n",
+      " [  1.82020441   1.82020441]\n",
+      " [ -2.98870335  -2.98870335]\n",
+      " [-11.73233297 -11.73233297]\n",
+      " [  0.77814665   0.77814665]\n",
+      " [ -2.05258066  -2.05258066]\n",
+      " [  0.5104916    0.5104916 ]\n",
+      " [ -1.81836092  -1.81836092]\n",
+      " [  1.40753462   1.40753462]\n",
+      " [  6.74233181   6.74233181]\n",
+      " [ -3.71859375  -3.71859375]\n",
+      " [  2.13758979   2.13758979]]\n",
+      "\n",
+      "The above two columns you get should be very similar.(Left-Your Numerical Gradient, Right-Analytical Gradient)\n",
+      "If your cost function implementation is correct, then the relative difference will be small (less than 1e-9).\n",
+      "\n",
+      "Relative Difference: 2.27377e-12\n"
+     ]
+    }
+   ],
    "source": [
     "#  Check gradients by running checkCostFunction\n",
     "utils.checkCostFunction(cofiCostFunc, 1.5)"
@@ -839,9 +1368,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 34,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Submitting Solutions | Programming Exercise anomaly-detection-and-recommender-systems\n",
+      "\n",
+      "Use token from last successful submission (ibrahimsharafelden@gmail.com)? (Y/n): Y\n",
+      "(3, 5)\n",
+      "(4, 5)\n",
+      "(4, 3)\n",
+      "(4, 3)\n",
+      "                                  Part Name |     Score | Feedback\n",
+      "                                  --------- |     ----- | --------\n",
+      "               Estimate Gaussian Parameters |   0 /  15 | \n",
+      "                           Select Threshold |   0 /  15 | \n",
+      "               Collaborative Filtering Cost |  20 /  20 | Nice work!\n",
+      "           Collaborative Filtering Gradient |  30 /  30 | Nice work!\n",
+      "                           Regularized Cost |  10 /  10 | Nice work!\n",
+      "                       Regularized Gradient |  10 /  10 | Nice work!\n",
+      "                                  --------------------------------\n",
+      "                                            |  70 / 100 |  \n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "grader[6] = cofiCostFunc\n",
     "grader.grade()"
@@ -858,9 +1413,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 36,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "New user ratings:\n",
+      "-----------------\n",
+      "Rated 4 stars: Toy Story (1995)\n",
+      "Rated 5 stars: Twelve Monkeys (1995)\n",
+      "Rated 3 stars: Usual Suspects, The (1995)\n",
+      "Rated 5 stars: Outbreak (1995)\n",
+      "Rated 3 stars: Shawshank Redemption, The (1994)\n",
+      "Rated 5 stars: While You Were Sleeping (1995)\n",
+      "Rated 5 stars: Forrest Gump (1994)\n",
+      "Rated 2 stars: Silence of the Lambs, The (1991)\n",
+      "Rated 2 stars: Alien (1979)\n",
+      "Rated 3 stars: Die Hard 2 (1990)\n",
+      "Rated 3 stars: Sphere (1998)\n"
+     ]
+    }
+   ],
    "source": [
     "#  Before we will train the collaborative filtering model, we will first\n",
     "#  add ratings that correspond to a new user that we just observed. This\n",
@@ -882,15 +1457,15 @@
     "\n",
     "# We have selected a few movies we liked / did not like and the ratings we\n",
     "# gave are as follows:\n",
-    "my_ratings[6] = 3\n",
-    "my_ratings[11]= 5\n",
-    "my_ratings[53] = 4\n",
-    "my_ratings[63] = 5\n",
-    "my_ratings[65] = 3\n",
+    "my_ratings[6] = 5\n",
+    "my_ratings[11]= 3\n",
+    "my_ratings[53] = 5\n",
+    "my_ratings[63] = 3\n",
+    "my_ratings[65] = 5\n",
     "my_ratings[68] = 5\n",
-    "my_ratings[182] = 4\n",
-    "my_ratings[225] = 5\n",
-    "my_ratings[354] = 5\n",
+    "my_ratings[182] = 2\n",
+    "my_ratings[225] = 3\n",
+    "my_ratings[354] = 3\n",
     "\n",
     "print('New user ratings:')\n",
     "print('-----------------')\n",
@@ -916,9 +1491,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 37,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Recommender system learning completed.\n"
+     ]
+    }
+   ],
    "source": [
     "#  Now, you will train the collaborative filtering model on a movie rating \n",
     "#  dataset of 1682 movies and 943 users\n",
@@ -979,9 +1562,42 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 38,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Top recommendations for you:\n",
+      "----------------------------\n",
+      "Predicting rating 5.0 for movie Aiqing wansui (1994)\n",
+      "Predicting rating 5.0 for movie Entertaining Angels: The Dorothy Day Story (1996)\n",
+      "Predicting rating 5.0 for movie They Made Me a Criminal (1939)\n",
+      "Predicting rating 5.0 for movie Great Day in Harlem, A (1994)\n",
+      "Predicting rating 5.0 for movie Star Kid (1997)\n",
+      "Predicting rating 5.0 for movie Prefontaine (1997)\n",
+      "Predicting rating 5.0 for movie Someone Else's America (1995)\n",
+      "Predicting rating 5.0 for movie Marlene Dietrich: Shadow and Light (1996)\n",
+      "Predicting rating 5.0 for movie Saint of Fort Washington, The (1993)\n",
+      "Predicting rating 5.0 for movie Santa with Muscles (1996)\n",
+      "\n",
+      "Original ratings provided:\n",
+      "--------------------------\n",
+      "Rated 4 for Toy Story (1995)\n",
+      "Rated 5 for Twelve Monkeys (1995)\n",
+      "Rated 3 for Usual Suspects, The (1995)\n",
+      "Rated 5 for Outbreak (1995)\n",
+      "Rated 3 for Shawshank Redemption, The (1994)\n",
+      "Rated 5 for While You Were Sleeping (1995)\n",
+      "Rated 5 for Forrest Gump (1994)\n",
+      "Rated 2 for Silence of the Lambs, The (1991)\n",
+      "Rated 2 for Alien (1979)\n",
+      "Rated 3 for Die Hard 2 (1990)\n",
+      "Rated 3 for Sphere (1998)\n"
+     ]
+    }
+   ],
    "source": [
     "p = np.dot(X, Theta.T)\n",
     "my_predictions = p[:, 0] + Ymean\n",
@@ -1002,6 +1618,13 @@
     "    if my_ratings[i] > 0:\n",
     "        print('Rated %d for %s' % (my_ratings[i], movieList[i]))"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -1020,7 +1643,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.4"
+   "version": "3.7.0"
   }
  },
  "nbformat": 4,