Generative Deep Learning
Overview
The definitive technical guide to building generative AI models — covering VAEs, GANs, diffusion models, transformers, and large language models from scratch.
Full Description
David Foster's 'Generative Deep Learning' (2nd Edition, O'Reilly) is the most comprehensive hands-on guide to building generative AI systems available. The book covers the full spectrum of generative architectures: Variational Autoencoders, Generative Adversarial Networks, normalising flows, diffusion models, transformers, and large language model fine-tuning. Each chapter comes with working Python/Keras code and builds toward real-world applications including image synthesis, music generation, text generation, and world models. Essential reading for any AI engineer working in generative AI.