Overview
- Explores variations of content generation AI, not just GANs
- Uses free online resources (such as Google Collaboratory) that allow users to train AI with GPUs on the cloud
- Is developer-focused, with lots of hands-on exercises (readers are encouraged to open the examples and run them while reading through the book)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (10 chapters)
Keywords
About this book
In this book we look at the many AI techniques capable of generating new realities. We start with the basics of deep learning. Then we move on to autoencoders and generative adversarial networks (GANs). We explore variations of GAN to generate content. The book ends with an in-depth look at the most popular generator projects.
By the end of this book you will understand the AI techniques used to generate different forms of content. You will be able to use these techniques for your own amusement or professional career to both impress and educate others around you and give you the ability to transform your own reality into something new.
What You Will Learn
- Know the fundamentals of content generation from autoencoders to generative adversarial networks (GANs)
- Explore variations of GAN
- Understand the basics of other forms of content generation
- Use advanced projects such as Faceswap, deepfakes, DeOldify, and StyleGAN2
Who This Book Is For
Machine learning developers and AI enthusiasts who want to understand AI content generation techniques
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Generating a New Reality
Book Subtitle: From Autoencoders and Adversarial Networks to Deepfakes
Authors: Micheal Lanham
DOI: https://doi.org/10.1007/978-1-4842-7092-9
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Micheal Lanham 2021
Softcover ISBN: 978-1-4842-7091-2Published: 16 July 2021
eBook ISBN: 978-1-4842-7092-9Published: 15 July 2021
Edition Number: 1
Number of Pages: XVII, 321
Number of Illustrations: 120 b/w illustrations
Topics: Machine Learning, Python