Java Deep Learning Cookbook

Constructing dense layers for input

The core of the neural network design is the layer architecture. For autoencoders, we need to design dense layers that do encoding at the front and decoding at the other end. Basically, we are reconstructing the inputs in this way. Accordingly, we need to make our layer design.

Let's start configuring our autoencoder using the default settings and then proceed further by defining the necessary input layers for our autoencoder. Remember that the number of incoming connections to the neural network will be equal to the number of outgoing connections from the neural network.