Generative deep learning teaching machines to paint, write, compose, and play
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),...
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Sebastopol, CA
O'Reilly Media, Incorporated
2023
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| Ausgabe: | Second edition. |
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| Online-Zugang: | lizenzpflichtig |
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| Zusammenfassung: | 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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| Beschreibung: | Includes bibliographical references and index. - Online resource; title from digital title page (viewed on May 22, 2023) |
| Beschreibung: | 1 online resource (xxvi, 426 pages) illustrations. |
| ISBN: | 9781098134143 1098134141 9781098134150 109813415X |