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.
