cnn-from-scratch

Building a convolutional neural network from scratch in an interactive way.

In this notebook, we're going to build a convolutional neural network for recognizing handwritten digits from scratch. By from scratch, I mean without using tensorflow's almighty neural network functions like tf.nn.conv2d. This way, you'll be able to uncover the blackbox and understand how CNN works more clearly. We'll use tensorflow interactively, so you can check the intermediate results along the way. This will also help your understanding.

Here are some functions implemented from scratch in this notebook.

1. Convolutional layer
2. ReLU
3. Max Pooling
4. Affine layer (Fully connected layer)
5. Softmax
6. Cross entropy error

You can view the notebook here