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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.
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Publisher : O’Reilly Media; 2nd edition (June 6, 2023)
Language : English
Paperback : 453 pages
ISBN-10 : 1098134184
ISBN-13 : 978-1098134181
Item Weight : 1.59 pounds
Dimensions : 7 x 0.92 x 9.19 inches
Customers say
Customers find the codebase great and helpful to implement. They say the book explains the principles behind algorithms clearly, is an excellent overview of the evolution of generative models, and has many well-sourced and working code and data examples. Readers also describe the content as amazing.
AI-generated from the text of customer reviews
