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Deep Learning with Python, Third Edition - Nyomtatható verzió +- HHW.hu (https://hhwforum.hu) +-- Fórum: Letöltések (https://hhwforum.hu/forumdisplay.php?fid=9) +--- Fórum: E-könyvek (https://hhwforum.hu/forumdisplay.php?fid=57) +---- Fórum: Külföldi könyvek (https://hhwforum.hu/forumdisplay.php?fid=64) +---- Téma: Deep Learning with Python, Third Edition (/showthread.php?tid=405094) |
RE: Deep Learning with Python, Third Edition - book24h - 2026-01-02 ![]() Free Download Deep Learning with Python, Third Edition by François Chollet and Matthew Watson English | 2025 | ISBN: 1633436586 | 648 pages | True EPUB | 22.78 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:
About the technology In less than a decade, deep learning has changed the world-twice. First, Python-based libraries like Keras, TensorFlow, and PyTorch elevated neural networks from lab experiments to high-performance production systems deployed at scale. And now, through Large Language Models and other generative AI tools, deep learning is again transforming business and society. In this new edition, Keras creator François Chollet invites you into this amazing subject in the fluid, mentoring style of a true insider. About the book Deep Learning with Python, Third Edition makes the concepts behind deep learning and generative AI understandable and approachable. This complete rewrite of the bestselling original includes fresh chapters on transformers, building your own GPT-like LLM, and generating images with diffusion models. Each chapter introduces practical projects and code examples that build your understanding of deep learning, layer by layer. What's inside
For readers with intermediate Python skills. No previous experience with machine learning or linear algebra required. About the author François Chollet is the co-founder of Ndea and the creator of Keras. Matthew Watson is a software engineer at Google working on Gemini and a core maintainer of Keras. Table of Contents 1 What is deep learning? 2 The mathematical building blocks of neural networks 3 Introduction to TensorFlow, PyTorch, JAX, and Keras 4 Classification and regression 5 Fundamentals of machine learning 6 The universal workflow of machine learning 7 A deep dive on Keras 8 Image classification 9 ConvNet architecture patterns 10 Interpreting what ConvNets learn 11 Image segmentation 12 Object detection 13 Timeseries forecasting 14 Text classification 15 Language models and the Transformer 16 Text generation 17 Image generation 18 Best practices for the real world 19 The future of AI 20 Conclusions Buy Premium From My Links To Get Resumable Support,Max Speed & Support Me Idézet:A kódrészlet megtekintéséhez be kell jelentkezned, vagy nincs jogosultságod a tartalom megtekintéséhez.Links are Interchangeable - Single Extraction |