GANs in Action

Chapter 2. Intro to generative modeling with autoencoders

This chapter covers

• Encoding data into a latent space (dimensionality reduction) and subsequent dimensionality expansion
• Understanding the challenges of generative modeling in the context of a variational autoencoder
• Generating handwritten digits by using Keras and autoencoders
• Understanding the limitations of autoencoders and motivations for GANs

I dedicate this chapter to my grandmother, Aurelie Langrova, who passed away as we were finishing the work on it. She will be missed dearly.

Jakub

You might be wondering why we chose to include this chapter in the book. There are three core reasons:

• Generative models are a new area for most. Most people who come across machine learning ...