Convolutional Neural Network

On the process of learning Deeplearning, i built Basic Convolutional Nural Network to get full understanding without help of ML library.

Overview

A Convolutional Neural Network written in Python, consisting of a single neuron that uses back propagation to learn. Just three layers are created which are convolution (conv for short), ReLU, and max pooling. The major steps involved are as follows:

1. Reading the input image.
2. Preparing filters.
3. Conv layer: Convolving each filter with the input image.
4. ReLU layer: Applying ReLU activation function on the feature maps (output of conv layer).
5. Max Pooling layer: Applying the pooling operation on the output of ReLU layer.
6. Stacking conv, ReLU, and max pooling layers.

You can have quick review with juputer notebook file.

Dependencies

• numpy.
• skimage.data (Just to Fetch image Data)
• matplotlib (For Displaying Output)

Credits

• Ahmed Gad blog.
• Andrew Ng
• Siraj Raval for his video