The goal of the current scenario, you're going to build a deeper neural network. This means you will add a hidden layer before the output one.
We've prepared the backbone of the code for you in the
neural_network.py file. The tasks have been pointed out.
The first task is to lead the MNIST dataset. You can use the
input_data.read_data_sets function. Use a path of your choice and the
The images are of the 28 x 28 size. The hidden layer has 1024 neurons and there are 10 labels.
image_size = 28
labels_size = 10
hidden_size = 1024