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Deep Learning with Python by Francois Chollet (2017, Trade Paperback)
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This is a NEW copy of DEEP LEARNING wih Python by Francois Chollet. Published by Manning Publications Co. LLC in 2018, this trade paperback covers deep learning techniques using the programming language Python.
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About this product
Product Identifiers
PublisherManning Publications Co. LLC
ISBN-101617294438
ISBN-139781617294433
eBay Product ID (ePID)236737376
Product Key Features
Number of Pages384 Pages
Publication NameDeep Learning with Python
LanguageEnglish
Publication Year2017
SubjectImage Processing, Intelligence (Ai) & Semantics, Programming Languages / Python
TypeTextbook
AuthorFrancois Chollet
Subject AreaComputers
FormatTrade Paperback
Dimensions
Item Height0.9 in
Item Weight23.3 Oz
Item Length9.2 in
Item Width7.6 in
Additional Product Features
Intended AudienceScholarly & Professional
LCCN2018-286242
Reviews'...is focused, concise and precise. It provides express and effective revision material and techniques without compromising the depth of your understanding.' Avis Whyte, Senior Research Fellow, University of Westminster 'An accessible quick revision guide with all the essential information in one place which makes a good addition to textbooks and other study material.' J oanne Atkinson, Director of Postgraduate Law Programmes, University of Portsmouth '... excellent companion for students. It is to be used as a revision guide and will be useful for students who are conversant with the principles and case law of each topic.' Alison Poole, Teaching Fellow, University of Portsmouth 'This series is great - after having revised everything, it showed me a way to condense all the information and gave me an idea of how I would go about structuring my essays.' Arama Lemon, Student, Coventry University 'The Law Express Q&A series is perfect as it targets different learning styles - it includes diagrams and flowcharts that you can follow for easy application with confidence. It's perfect for anyone who wants to receive an extra boost with their revision!' Mariam Hussain, Student, University of Westminster
Dewey Edition23
IllustratedYes
Dewey Decimal005.133
SynopsisSummary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning--a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. 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 Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences 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 is one of the most important researchers in modern day deep learning. His groundbreaking work includes the creation of the Keras deep learning library, and major contributions to the TensorFlow framework. These tools have helped revolutionize and democratize deep learning. François is an AI researcher and Senior Staff Software Engineer at Google. François authored Deep Learning with R alongside J.J. Allaire, and developed the Abstraction and Reasoning Challenge that measures AI skill-acquisition on unknown tasks. Table of Contents What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance PART 1 - FUNDAMENTALS OF DEEP LEARNING PART 2 - DEEP LEARNING IN PRACTICE From the Publisher For over thirty years, Manning Publications has been delivering impeccable quality in tech publishing. Our rich and independent history is filled with innovations, including groundbreaking early access programs, DRM-free ebooks, and live learning projects. We spend thousands of hours making each Manning book outstanding--and our readers agree! We're regularly told that Manning produces the very best tech content you can buy. Manning authors are technology experts, including distinguished academics, industry veterans, and the creators of major tools. Timeless Manning classics include Francois Chollet's Deep Learning with Python , Jon Skeet's C# in Depth , Don Jones' Learn Windows Powershell in a Month of Lunches , and Chris Richarson's Microservices Patterns . We're proud to help some of the world's greatest programmers share their unique insight with you., DESCRIPTION Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. Deep Learning with Python is structured around a series of practical code examples that illustrate each new concept introduced and demonstrate best practices. By the time you reach the end of this book, you will have become a Keras expert and will be able to apply deep learning in your own projects. KEY FEATURES * Practical code examples * In-depth introduction to Keras * Teaches the difference between Deep Learning and AI ABOUT THE TECHNOLOGY Deep learning is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more. AUTHOR BIO Francois Chollet is the author of Keras, one of the most widely used libraries for deep learning in Python. He has been working with deep neural networks since 2012. Francois is currently doing deep learning research at Google. He blogs about deep learning at blog.keras.io., Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher Fran ois Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning--a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher Fran ois Chollet, this book builds your understanding through intuitive explanations and practical examples. 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 Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences 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 Fran ois 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 deep-learning research, with a focus on computer vision and the application of machine learning to formal 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. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance, Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. Deep Learning with Python is structured around a series of practical code examples that illustrate each new concept introduced and demonstrate best practices. By the time you reach the end of this book, you will have become a Keras expert and will be able to apply deep learning in your own projects. KEY FEATURES * Practical code examples * In-depth introduction to Keras * Teaches the difference between Deep Learning and AI ABOUT THE TECHNOLOGY Deep learning is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more. AUTHOR BIO Francois Chollet is the author of Keras, one of the most widely used libraries for deep learning in Python. He has been working with deep neural networks since 2012. Francois is currently doing deep learning research at Google. He blogs about deep learning at blog.keras.io., DESCRIPTIONDeep learning is applicable to a widening range of artificialintelligence problems, such as image classification, speech recognition,text classification, question answering, text-to-speech, and opticalcharacter recognition. Deep Learning with Python is structured around a series of practicalcode examples that illustrate each new concept introduced anddemonstrate best practices. By the time you reach the end of this book,you will have become a Keras expert and will be able to apply deeplearning in your own projects. KEY FEATURES * Practical code examples* In-depth introduction to Keras* Teaches the difference between Deep Learning and AI ABOUT THE TECHNOLOGYDeep learning is the technology behind photo tagging systems atFacebook and Google, self-driving cars, speech recognition systems onyour smartphone, and much more. AUTHOR BIOFrancois Chollet is the author of Keras, one of the most widely usedlibraries for deep learning in Python. He has been working with deep neuralnetworks since 2012. Francois is currently doing deep learning research atGoogle. He blogs about deep learning at blog.keras.io.
LC Classification NumberQ325.5
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- Oct 03, 2019
Book paper and print quality is a low cost version of the book.
Ordered a book published by from Manning publication. The book received was new as described but based on paper and print quality, I can tell its definitely a low cost print version of the book. I have several other books from Manning publication, so I can make out the difference quite easily. If I had known this earlier, I would have spent a few extra dollars or bought a used version of better print version of the book.Verified purchase: YesCondition: New
- Mar 25, 2020
Great book to start coding right away!
This is a great hands-on practical book. Very practical good to start implementing deep learning.Verified purchase: YesCondition: Pre-owned
- Feb 23, 2021
ok
okVerified purchase: YesCondition: Pre-owned
