Generating a New Reality
eBook - ePub

Generating a New Reality

From Autoencoders and Adversarial Networks to Deepfakes

  1. English
  2. ePUB (mobile friendly)
  3. Only available on web
eBook - ePub

Generating a New Reality

From Autoencoders and Adversarial Networks to Deepfakes

Book details
Table of contents
Citations

About This Book

The emergence of artificial intelligence (AI) has brought us to the precipice of a new age where we struggle to understand what is real, from advanced CGI in movies to even faking the news. AI that was developed to understand our reality is now being used to create its own reality.
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

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Yes, you can access Generating a New Reality by Micheal Lanham in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Apress
Year
2021
ISBN
9781484270929

Table of contents

  1. Cover
  2. Front Matter
  3. 1. The Basics of Deep Learning
  4. 2. Unleashing Generative Modeling
  5. 3. Exploring the Latent Space
  6. 4. GANs, GANs, and More GANs
  7. 5. Image to Image Content Generation
  8. 6. Residual Network GANs
  9. 7. Attention Is All We Need!
  10. 8. Advanced Generators
  11. 9. Deepfakes and Face Swapping
  12. 10. Cracking Deepfakes
  13. Back Matter