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Deep Learning with Python by François Chollet (2021, Trade Paperback)

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eBay item number:404920198182
Last updated on 07 Jun, 2024 07:45:54 AESTView all revisionsView all revisions

Item specifics

Condition
Brand new: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
ISBN
9781617296864

About this product

Product Identifiers

Publisher
Manning Publications Co. LLC
ISBN-10
1617296864
ISBN-13
9781617296864
eBay Product ID (ePID)
4050404173

Product Key Features

Number of Pages
400 Pages
Publication Name
Deep Learning with Python
Language
English
Publication Year
2021
Subject
Neural Networks, Programming Languages / Python
Type
Textbook
Subject Area
Computers
Author
François Chollet
Format
Trade Paperback

Dimensions

Item Height
1.3 in
Item Weight
38.1 Oz
Item Length
9.3 in
Item Width
7.3 in

Additional Product Features

LCCN
2021-425412
Reviews
"The first edition of Deep Learning with Python is one of the best books on the subject. The second edition made it even better. " Todd Cook "Really easy to read and gives practical examples and easy to understand explanations of the concepts behind deep learning." Billy O'Callaghan "A tell-tale book that tells you all the secrets of deep learning!" Nikos Kanakaris "A great refresher of the old concepts explored in new and exciting ways. Manifold hypothesis steals the show!" Sayak Paul "One of the best books on this topic." Rauhsan Jha "The book is full of insights, useful both for the novice and the more experienced machine learning professional." Viton Vitanis "This is the book to read if you want to learn DL." Kjell Jansson "Francois explains everything in a very lucid & systematic manner, this approach of writing certainly gives confidence in users." Rauhsan Jha
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
005.133
Synopsis
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., Printed in full color! Unlock the groundbreaking advances of deep learning with this extensively revised new edition of the bestselling original. Learn directly from the creator of Keras and master practical Python deep learning techniques that are easy to apply in the real world. In Deep Learning with Python, Second Edition you will learn: Deep learning from first principles Image classification and image segmentation Timeseries forecasting Text classification and machine translation Text generation, neural style transfer, and image generation Full color printing throughout Deep Learning with Python has taught thousands of readers how to put the full capabilities of deep learning into action. This extensively revised full color second edition introduces deep learning using Python and Keras, and is loaded with insights for both novice and experienced ML practitioners. You'll learn practical techniques that are easy to apply in the real world, and important theory for perfecting neural networks. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology 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. About the book 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 color illustrations, and clear examples. You'll quickly pick up the skills you need to start developing deep-learning applications. What's inside Deep learning from first principles Image classification and image segmentation Time series forecasting Text classification and machine translation Text generation, neural style transfer, and image generation Full color printing throughout About the reader For readers with intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the author François Chollet is a software engineer at Google and creator of the Keras deep-learning library. Table of 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, "The first edition of Deep Learning with Python is one of the best books on the subject. The second edition made it even better." - Todd Cook 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.
LC Classification Number
Q325.5.C4 2022

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