adds contents table in learning notebook

Author: SnShine

learning.ipynb

@@ -50,7 +50,20 @@
     "\n",
     "In Reinforcement Learning the agent learns from a series of reinforcements—rewards or punishments.\n",
     "\n",
-    "**Example**: Let's talk about an agent to play the popular Atari game—[Pong](http://www.ponggame.org). We will reward a point for every correct move and deduct a point for every wrong move from the agent. Eventually, the agent will figure out its actions prior to reinforcement were most responsible for it."
+    "**Example**: Let's talk about an agent to play the popular Atari game—[Pong](http://www.ponggame.org). We will reward a point for every correct move and deduct a point for every wrong move from the agent. Eventually, the agent will figure out its actions prior to reinforcement were most responsible for it.\n",
+    "\n",
+    "## Contents\n",
+    "\n",
+    "* Explanations of learning module\n",
+    "* Practical Machine Learning Task\n",
+    "    * MNIST handwritten digits classification\n",
+    "        * Loading and Visualising digits data\n",
+    "        * Naive kNN classifier\n",
+    "        * Overfitting and how to avoid it\n",
+    "            * Train-Test split\n",
+    "            * Crossvalidation\n",
+    "            * Regularisation\n",
+    "    * Email spam detector"
    ]
   },
   {