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.gitignore

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# Data for TensorFlow
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data/
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# PyCharm
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.idea/
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# Byte-compiled / optimized / DLL files
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__pycache__/

02_Convolutional_Neural_Network.ipynb

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}
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],
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"source": [
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"from IPython.display import Image\n",
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"Image('images/02_convolution.png')"
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"There are 50.000 images in the training-set. It takes a long time to calculate the gradient of the model using all these images. We therefore only use a small batch of images in each iteration of the optimizer.\n",
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"There are 55.000 images in the training-set. It takes a long time to calculate the gradient of the model using all these images. We therefore only use a small batch of images in each iteration of the optimizer.\n",
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"\n",
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"If your computer crashes or becomes very slow because you run out of RAM, then you may try and lower this number, but you may then need to perform more optimization iterations."
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README.md

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## Contents
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* Simple Linear Model ([Jupyter Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/01_Simple_Linear_Model.ipynb))
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1. Simple Linear Model ([Jupyter Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/01_Simple_Linear_Model.ipynb))
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* Convolutional Neural Networks ([Jupyter Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/02_Convolutional_Neural_Network.ipynb))
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2. Convolutional Neural Network ([Jupyter Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/02_Convolutional_Neural_Network.ipynb))
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## Videos
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