Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play, 2/e (Paperback)

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 for text-to-image generation

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.

生成式人工智慧（Generative AI）是科技界最熱門的話題。這本實用書籍教導機器學習工程師和資料科學家如何使用TensorFlow和Keras從頭開始創建令人印象深刻的生成式深度學習模型，包括變分自編碼器（VAEs）、生成對抗網絡（GANs）、Transformer、正規化流、基於能量的模型和去噪擴散模型。

本書從深度學習的基礎知識開始，逐步介紹最前沿的架構。通過技巧和訣竅，您將了解如何使模型學習更高效並變得更有創造力。

- 發現VAEs如何改變照片中的面部表情
- 訓練GANs根據自己的數據集生成圖像
- 構建擴散模型以生成新品種的花朵
- 訓練自己的GPT進行文本生成
- 了解像ChatGPT這樣的大型語言模型是如何訓練的
- 探索StyleGAN2和ViT-VQGAN等最先進的架構
- 使用Transformer和MuseGAN創作多聲部音樂
- 理解生成式世界模型如何解決強化學習任務
- 深入研究多模態模型，如DALL.E 2、Imagen和Stable Diffusion，用於文本到圖像的生成

本書還探討了生成式人工智慧的未來以及個人和企業如何主動利用這一令人驚嘆的新技術創造競爭優勢。