GANs in Action: Deep learning with Generative Adversarial Networks cover

About this book

The goal of this book is to provide the definitive guide for anyone interested in learning about Generative Adversarial Networks (GANs) from the ground up. Starting from the simplest examples, we advance to some of the most innovative GAN implementations and techniques. We make cutting-edge research accessible by providing the intuition behind these advances while sparing you all but the essential math and theory.

Ultimately, our goal is to give you the knowledge and tools necessary not only to understand what has been accomplished in GANs to date, but also to empower you to find new applications of your choosing. The generative adversarial paradigm is full of potential to be unraveled by enterprising individuals like you who can make an impact through academic and real-world applications alike. We are thrilled to have you join us on this journey.

Who should read this book

This book is intended for readers who already have some experience with machine learning and neural networks. The following list indicates what you should ideally know. Although we try our best to explain most things as we go, you should be confident about at least 70% of this list:

About the code

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Other online resources

How this book is organized: a roadmap

About the authors



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