Deep learning with Python / François Chollet.

Format:

Book

Author/Creator:

Chollet, François, author.

Language:

English

Subjects (All):

Python (Computer program language).

Machine learning.

Neural networks (Computer science).

Computer programming.

Physical Description:

1 online resource (xxiii, 478 pages) : illustrations.

Edition:

Second edition.

Place of Publication:

Shelter Island, New York : Manning Publications Co. LLC, 2021.

Summary:

The bestseller revised! Deep Learning with Python, second edition is a comprehensive introduction to the field of deep learning using Python and the powerful Keras library. Written by Google AI researcher François Chollet, the creator of Keras, this revised edition has been updated with new chapters, new tools, and cutting-edge techniques drawn from the latest research. You’ll build your understanding through practical examples and intuitive explanations that make the complexities of deep learning accessible and understandable. about the technology: Machine learning has made remarkable progress in recent years. We’ve gone from near-unusable speech recognition, to near-human accuracy. From machines that couldn't beat a serious Go player, to defeating a world champion. Medical imaging diagnostics, weather forecasting, and natural language question answering have suddenly become tractable problems. Behind this progress is deep learning - a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications across every industry sector. about the book: Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. You’ll learn directly from the creator of Keras, François Chollet, building your understanding through intuitive explanations and practical examples. Updated from the original bestseller with over 50% new content, this second edition includes new chapters, cutting-edge innovations, and coverage of the very latest deep learning tools. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. what's inside: Deep learning from first principles; Image-classification, imagine segmentation, and object detection; Deep learning for natural language processing; Timeseries forecasting; Neural style transfer, text generation, and image generation. about the reader: Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. about the author: François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does AI research, with a focus on abstraction and reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others.

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

Index.

Notes:

Includes index.

Description based on print version record.

ISBN:

9781638350095

1638350094

9781617296864

1617296864

OCLC:

1296760900

Publisher Number:

9781617296864 (paperback)