GANs in Action

Part 1. Introduction to GANs and generative modeling

Part 1 introduces the world of Generative Adversarial Networks (GANs) and walks through implementations of the most canonical GAN variants:

• In chapter 1, you will learn the basics of GANs and develop an intuitive understanding of how they work.
• In chapter 2, we will switch gears a little and look at autoencoders, so you can get a more holistic understanding of generative modeling. Autoencoders are some of the most important theoretical and practical precursors to GANs and continue to be widely used to this day.
• Chapter 3 starts where chapter 1 left off and dives deeper into the theory underlying GANs and adversarial learning. In this chapter, you will also implement and train your first, ...