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Deep Learning with Python Paperback – Dec 22 2017

4.6 4.6 out of 5 stars 1,359 ratings

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From the Publisher

Deep Learning with Python

Who should read this book

  • If you’re a data scientist familiar with machine learning, this book will provide you with a solid, practical introduction to deep learning, the fastest-growing and most significant subfield of machine learning
  • If you’re a deep-learning expert looking to get started with the Keras framework, you’ll find this book to be the best Keras crash course available
  • If you’re a graduate student studying deep learning in a formal setting, you’ll find this book to be a practical complement to your education, helping you build intuition around the behavior of deep neural networks and familiarizing you with key best practices

About This Book

This book was written for anyone who wishes to explore deep learning from scratch or broaden their understanding of deep learning. Whether you’re a practicing machine-learning engineer, a software developer, or a college student, you’ll find value in these pages. This book offers a practical, hands-on exploration of deep learning. It avoids mathematical notation, preferring instead to explain quantitative concepts via code snippets and to build practical intuition about the core ideas of machine learning and deep learning. You’ll learn from more than 30 code examples that include detailed commentary, practical recommendations, and simple high-level explanations of everything you need to know to start using deep learning to solve concrete problems. The code examples use the Python deep-learning framework Keras, with Tensor- Flow as a back-end engine. Keras, one of the most popular and fastest-growing deeplearning frameworks, is widely recommended as the best tool to get started with deep learning.

After reading this book, you’ll have a solid understand of what deep learning is, when it’s applicable, and what its limitations are. You’ll be familiar with the standard workflow for approaching and solving machine-learning problems, and you’ll know how to address commonly encountered issues. You’ll be able to use Keras to tackle real-world problems ranging from computer vision to natural-language processing: image classification, timeseries forecasting, sentiment analysis, image and text generation, and more.

This book is written for people with Python programming experience who want to get started with machine learning and deep learning. But this book can also be valuable to many different types of readers. Even technically minded people who don’t code regularly will find this book useful as an introduction to both basic and advanced deep-learning concepts.

In order to use Keras, you’ll need reasonable Python proficiency. Additionally, familiarity with the Numpy library will be helpful, although it isn’t required. You don’t need previous experience with machine learning or deep learning: this book covers from scratch all the necessary basics. You don’t need an advanced mathematics background, either—high school–level mathematics should suffice in order to follow along.

Deep Learning with Python machine learning Deep Learning with R machine learning
Deep Learning with Python Deep Learning with R
Deep Learning with Francois Chollet

Product description

About the Author

François Chollet is a software engineer at Google and creator of Keras.

Product details

  • ASIN ‏ : ‎ 1617294438
  • Publisher ‏ : ‎ Manning; First Edition (Dec 22 2017)
  • Language ‏ : ‎ English
  • Paperback ‏ : ‎ 384 pages
  • ISBN-10 ‏ : ‎ 9781617294433
  • ISBN-13 ‏ : ‎ 978-1617294433
  • Item weight ‏ : ‎ 100 g
  • Dimensions ‏ : ‎ 18.75 x 2.03 x 23.5 cm
  • Customer Reviews:
    4.6 4.6 out of 5 stars 1,359 ratings

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Customer reviews

4.6 out of 5 stars
4.6 out of 5
1,359 global ratings

Top reviews from Canada

Reviewed in Canada 🇨🇦 on October 14, 2022
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Reviewed in Canada 🇨🇦 on June 14, 2019
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3.0 out of 5 stars Book layout is awful, but book content is amazing
Reviewed in Canada 🇨🇦 on June 14, 2019
Don't get me wrong the book itself is AMAZING, its just the way its printed is completely awful. Every left page is so close to the middle I have to bend left pages very hard just so i can read it comfortably. EVERY LEFT PAGE.

But book itself is amazing and I will 100% suggest it to anyone who wants to get into Machine Deep Learning.
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Reviewed in Canada 🇨🇦 on November 23, 2018
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5.0 out of 5 stars Excellent and refreshingly unpretentious
Reviewed in Australia 🇦🇺 on October 19, 2020
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Prasetyo Aji
5.0 out of 5 stars the package is good and fast delivery
Reviewed in Japan 🇯🇵 on August 5, 2019
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Mel Li
5.0 out of 5 stars Very good book
Reviewed in Australia 🇦🇺 on September 27, 2020
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5.0 out of 5 stars とても良い実践書
Reviewed in Japan 🇯🇵 on November 11, 2018
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2 people found this helpful
5.0 out of 5 stars The best introduction to this very interesting field that I have found
Reviewed in the United Kingdom 🇬🇧 on February 7, 2018
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12 people found this helpful