Generating a New Reality: From Autoencoders and Adversarial Networks to Deepfakes - Softcover

Lanham, Micheal

 
9781484270912: Generating a New Reality: From Autoencoders and Adversarial Networks to Deepfakes
Softcover
ISBN 10: 1484270916 ISBN 13: 9781484270912
Verlag: Apress, 2021

Inhaltsangabe

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

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Über die Autorin bzw. den Autor

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.

Von der hinteren Coverseite

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.

Youwill:
  • 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



„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Verlag
Apress
Erscheinungsdatum
2021
Sprache
Englisch
ISBN 10 
1484270916
ISBN 13 
9781484270912
Einband
Taschenbuch
Auflage
1
Anzahl der Seiten
340
Kontakt zum Hersteller
ProductSafety@springernature.com
ProductSafety@springernature.com

Poststr. 9
Darmstadt
64293
Deutschland

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