TensorFlow in a Nutshell -- Part Three: All the Models

These networks consist of perceptrons in layers that take inputs that pass information on to the next layer. The last layer in the network produces the output. There is no connection between each node in a given layer. The layer that has no original input and no final output is called the hidden layer. The goal of this network is similar to other supervised neural networks using back propagation, to make inputs have the desired trained outputs.