├── README.md
└── demonotes.ipynb


/README.md:
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 1 | # How_to_make_a_tensorflow_image_classifier_LIVE
 2 | 
 3 | ##Overview
 4 | 
 5 | This is the code for [this](https://www.youtube.com/watch?v=APmF6qE3Vjc) video by Siraj Raval on Youtube. This Jupyter notebook shows step by step, the process of building a Convolutional Neural Network using Tensorflow to classify [MNIST](http://yann.lecun.com/exdb/mnist/) digits.
 6 | 
 7 | ##Dependencies
 8 | 
 9 | * matplotlib
10 | * tensorflow 
11 | * numpy 
12 | * scikit-learn
13 | * math
14 | 
15 | install missing dependencies with [pip](https://pip.pypa.io/en/stable/). And install tensorflow via [this](https://www.tensorflow.org/install/) link. 
16 | 
17 | ##Usage
18 | 
19 | Once dependencies are installed run `jupyter notebook` in terminal to see the code in your browser. 
20 | 
21 | ##Credits
22 | 
23 | Credits for this code go to [Hvass Labs](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/02_Convolutional_Neural_Network.ipynb) I've merely created a wrapper to get people started
24 | 


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