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Deep learning with Python

By: Material type: TextTextPublication details: New York : Manning, ©2021Edition: 2nd edDescription: xxiii, 478 p. : col. ill. ; 24 cmISBN:
  • 9781617296864
Subject(s): DDC classification:
  • 005.133 23 CHO-D
LOC classification:
  • QA76.73.P98 C465 2021
Contents:
1. What is deep learning? -- 2. The mathematical building blocks of neural networks -- 3. Introduction to Keras and TensorFlow -- 4. Getting started with neural networks: classification and regression -- 5. Fundamentals of machine learning -- 6. The universal workflow of machine learning -- 7. Working with Keras: a deep dive -- 8. Introduction to deep learning for computer vision -- 9. Advanced deep learning for computer vision -- 10. Deep learning for timeseries -- 11. Deep learning for text -- 12. Generative deep learning -- 13. Best practices for the real world -- 14. Conclusions.
Summary: Recent innovations in deep learning unlock exciting new software capabilities like automated language translation, image recognition, and more. Deep learning is quickly becoming essential knowledge for every software developer, and modern tools like Keras and TensorFlow put it within your reach-- even if you have no background in mathematics or data science. This book shows you how to get started. "Deep learning with Python, second edition" introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras creator François Chollet offers insights for both novice and experienced machine learning practitioners. As you move through this book, you'll build your understanding through intuitive explanations, crisp illustrations, and clear examples. You'll quickly pick up the skills you need to start developing deep-learning applications.--
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
Books Books IIITD General Stacks Computer Science and Engineering 005.133 CHO-D (Browse shelf(Opens below)) Available 011099
Total holds: 0

Previous edition: 2018.

Includes index.

1. What is deep learning? -- 2. The mathematical building blocks of neural networks -- 3. Introduction to Keras and TensorFlow -- 4. Getting started with neural networks: classification and regression -- 5. Fundamentals of machine learning -- 6. The universal workflow of machine learning -- 7. Working with Keras: a deep dive -- 8. Introduction to deep learning for computer vision -- 9. Advanced deep learning for computer vision -- 10. Deep learning for timeseries -- 11. Deep learning for text -- 12. Generative deep learning -- 13. Best practices for the real world -- 14. Conclusions.

Recent innovations in deep learning unlock exciting new software capabilities like automated language translation, image recognition, and more. Deep learning is quickly becoming essential knowledge for every software developer, and modern tools like Keras and TensorFlow put it within your reach-- even if you have no background in mathematics or data science. This book shows you how to get started. "Deep learning with Python, second edition" introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras creator François Chollet offers insights for both novice and experienced machine learning practitioners. As you move through this book, you'll build your understanding through intuitive explanations, crisp illustrations, and clear examples. You'll quickly pick up the skills you need to start developing deep-learning applications.--

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