Deep Learning with Python, Third Edition (MEAP V04)

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Free Download Deep Learning with Python, Third Edition (MEAP V04) By François Chollet and Matthew Watson
English | 2025 | ISBN: 9781633436589 | 903 pages | PDF,EPUB | 77.22 MB
The bestselling book on Python deep learning, now covering generative AI, Keras 3, PyTorch, and JAX!

Deep Learning with Python, Third Edition puts the power of deep learning in your hands. This new edition includes the latest Keras and TensorFlow features, generative AI models, and added coverage of PyTorch and JAX. Learn directly from the creator of Keras and step confidently into the world of deep learning with Python.
In Deep Learning with Python, Third Edition you'll discover
Deep learning from first principles
The latest features of Keras 3
A primer on JAX, PyTorch, and TensorFlow
Image classification and image segmentation
Time series forecasting
Large Language models
Text classification and machine translation
Text and image generation-build your own GPT and diffusion models!
Scaling and tuning models
With over 100,000 copies sold, Deep Learning with Python makes it possible for developers, data scientists, and machine learning enthusiasts to put deep learning into action. In this expanded and updated third edition, Keras creator François Chollet offers insights for both novice and experienced machine learning practitioners. You'll master state-of-the-art deep learning tools and techniques, from the latest features of Keras 3 to building AI models that can generate text and images.
about the book
Deep Learning with Python, Third Edition introduces deep learning from scratch. Each chapter introduces practical code examples that build up your understanding of deep learning layer by layer. You'll appreciate the intuitive explanations, crisp color illustrations, and clear examples. In this expanded third edition you'll find fresh chapters on the transformers architecture, building your own GPT-like large language model, and image generation with diffusion models. Plus, even DL veterans will benefit from the insightful explanations on the nature of deep learning.

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