The Generative Deep Learning Book
Teaching Machines To Paint, Write, Compose and Play
The Book
Generative AI is the hottest topic in tech. This practical book teaches machine learning engineers and data scientists how to create impressive generative deep learning models from scratch using Tensorflow and Keras, 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, readers can make their models learn more efficiently and become more creative.
The 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.
David Foster
David is experienced in the design and implementation of advanced statistical and machine learning techniques. He holds an MA in Mathematics from Cambridge and an MSc in Operational Research.
What's covered?
✅ Discover how VAEs can change facial expressions
✅ Train GANs to generate images based on your dataset
✅ Build diffusion models to produce new flower varieties
✅ Train your own GPT for text generation
✅ Compose music using Transformers and MuseGAN
✅ Understand how generative world models can solve reinforcement learning tasks
✅ DALL.E 2, Imagen and Stable Diffusion for text-to-image generation
Get your copy today!
Learn how to build your very own creative generative models with this practical guide.