Generative Deep Learning: Teaching Machines To Paint, Write, Compose, and Play 2nd Edition
Author(s): David Foster (Author)
- Publisher: O'Reilly Media
- Publication Date: June 6, 2023
- Edition: 2nd
- Language: English
- Print length: 453 pages
- ISBN-10: 1098134184
- ISBN-13: 9781098134181
Book Description
Generative AI is the hottest topic in tech. This practical book teaches machine learning engineers and data scientists how to use TensorFlow and Keras to create impressive generative deep learning models from scratch, including variational autoencoders (VAEs), generative adversarial networks (GANs), Transformers, normalizing flows, energy-based models, and denoising diffusion models.
The book starts with the basics of deep learning and progresses to cutting-edge architectures. Through tips and tricks, you’ll understand how to make your models learn more efficiently and become more creative.
- Discover how VAEs can change facial expressions in photos
- Train GANs to generate images based on your own dataset
- Build diffusion models to produce new varieties of flowers
- Train your own GPT for text generation
- Learn how large language models like ChatGPT are trained
- Explore state-of-the-art architectures such as StyleGAN2 and ViT-VQGAN
- Compose polyphonic music using Transformers and MuseGAN
- Understand how generative world models can solve reinforcement learning tasks
- Dive into multimodal models such as DALL.E 2, Imagen, and Stable Diffusion
This book also explores the future of generative AI and how individuals and companies can proactively begin to leverage this remarkable new technology to create competitive advantage.
Editorial Reviews
Review
Head of Strategy, Stability AI
This book is becoming part of my life. On finding a copy in my living room I asked my son: “when did you get this?”. He replied, “when you gave it to me”, bemused by my senior moment. Going through various sections together, I came to regard Generative Deep Learning as the ‘Gray’s Anatomy’ of Generative AI.
The author dissects the anatomy of Generative AI with an incredible clarity and reassuring authority. He offers a truly remarkable account of a fast-moving field, underwritten with pragmatic examples, engaging narratives and references that are so current, it reads like a living history.
Throughout his deconstructions, the author maintains a sense of wonder and excitement about the potential of Generative AI – especially evident in the book’s compelling dénouement: having laid bare the technology, the author reminds us that we are at the dawn of a new age of intelligence. An age in which Generative AI holds a mirror up to our language, our art, our creativity; reflecting not just what we have created, but what we could create — what we can create — limited only by “your own imagination”.
The central theme of generative models in artificial intelligence resonates deeply with me, because I see exactly the same themes emerging in the natural sciences; namely, a view of ourselves as generative models of our lived world. I suspect – in the next edition of this book — we will read about the confluence of artificial and natural intelligence. Until that time, I will keep this edition next to my Gray’s Anatomy, and other treasures on my bookshelf.
Karl Friston, FRSProfessor of Neuroscience, University College London.
Generative AI is reshaping countless industries and powering a new generation of creative tools. This book is the perfect way to get going with generative modeling and start building with this revolutionary technology yourself.
Ed Newton-RexVP Audio at Stability AI and composer
An excellent book that dives right into all of the major techniques behind state-of-the-art generative deep learning. You’ll find intuitive explanations and clever analogies — backed by didactic, highly readable code examples. An exciting exploration of one of the most fascinating domains in AI!
Generative AI is the next revolutionary step in AI technology that will have a massive impact on the world. This book provides a great introduction to this field and its incredible potential and potential risks.
About the Author
Through ADSP, David leads the delivery of high-profile data science and AI projects across the public and private sectors. He has won several international machine-learning competitions and is a faculty member of the Machine Learning Institute. He has given talks internationally on topics related to the application of cutting-edge data science and AI within industry and academia.
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