Generating a New Reality
Apress (Verlag)
978-1-4842-7091-2 (ISBN)
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
Micheal Lanham is a proven software and tech innovator with more than 20 years of experience. During that time, he has developed a broad range of software applications in areas including games, graphics, web, desktop, engineering, artificial intelligence (AI), GIS, and machine learning (ML) applications for a variety of industries as an R&D developer. At the turn of the millennium, Micheal began working with neural networks and evolutionary algorithms in game development. He is an avid educator, has written more than eight books covering game development, extended reality, and AI, and teaches at meetups and other events. Micheal also likes to cook for his large family in his hometown of Calgary, Canada.
Chapter 1: The Basics of Deep Learning.- Chapter 2: Unleashing Generative Modeling.- Chapter 3: Exploring the Latent Space.- Chapter 4: GANs, GANs, and More GANs.- Chapter 5: Image to Image Generation with GANs.- Chapter 6: Residual Network GANs.- Chapter 7: Attention Is All We Need.- Chapter 8: Advanced Generators.- Chapter 9: Deepfakes and Faceswapping.- Chapter 10: Cracking Deepfakes.- Appendix A: Running Google Colab Locally.- Appendix B: Opening a Notebook.- Appendix C: Connecting Google Drive and Saving.
| Erscheinungsdatum | 23.07.2021 |
|---|---|
| Zusatzinfo | 120 Illustrations, black and white; XVII, 321 p. 120 illus. |
| Verlagsort | Berkley |
| Sprache | englisch |
| Maße | 178 x 254 mm |
| Themenwelt | Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Schlagworte | Adversarial Latent Encoders • Autoencoders • Avatarify • Conditional GAN • CycleGAN • deepfake • DeOldify • First Order Model Motion • generative adversarial networks • Pix2Pix • Self Attention GAN • StyleGAN |
| ISBN-10 | 1-4842-7091-6 / 1484270916 |
| ISBN-13 | 978-1-4842-7091-2 / 9781484270912 |
| Zustand | Neuware |
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