The simple neural network that we are going to build will contain an input and output layer (as does any neural network). The network will include a single hidden layer between the input and output layer. This architecture is depicted as follows:
In particular, we are going to include four nodes in the input layer, three nodes in the hidden layer, and three nodes in the output layer. The four nodes in the input layer correspond to the number of attributes that we are going to feed into the network. Think about these four inputs as something like the four measurements we used to classify iris flowers in Chapter 5, Classification ...
