Deep Learning By Example

Autoencoder architectures

As we mentioned, a typical autoencoder consists of three parts. Let's explore these three parts in more detail. To motivate you, we are not going to reinvent the wheel here in this chapter. The encoder-decoder part is nothing but a fully connected neural network, and the code part is another neural network but it's not fully connected. The dimensionality of this code part is controllable and we can treat it as a hyperparameter:

Figure 3: General encoder-decoder architecture of autoencoders

Before diving into using autoencoders for compressing the MNIST dataset, we are going to list the set of hyperparameters that ...