Deep Learning with Keras

Improving the simple net in Keras with hidden layers

We have a baseline accuracy of 92.36% on training, 92.27% on validation, and 92.22% on the test. This is a good starting point, but we can certainly improve it. Let's see how.

A first improvement is to add additional layers to our network. So, after the input layer, we have a first dense layer with the N_HIDDEN neurons and an activation function relu. This additional layer is considered hidden because it is not directly connected to either the input or the output. After the first hidden layer, we have a second hidden layer, again with the N_HIDDEN neurons, followed by an output layer with 10 neurons, each of which will fire when the relative digit is recognized. The following code defines ...