This is a Jupyter Notebook for MNIST handwritten digit recognition.
The algorithm builds a deep neural network with 4 hidden layer and 1 output layer.
The activation function for the hidden layer is ReLU and the output layer is softmax.
Number of hidden nodes for each layer can be specified/modified form the given. However the code presented here sets the number of hidden nodes for each layer to 500. It runs for 20 epochs and it achieves an accuracy of 0.9437.