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Deep Learning with Python, Second Edition Paperback – Dec 21 2021

4.6 4.6 out of 5 stars 245 ratings

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From the Publisher

Chollet is a master of pedagogy....... a joy to read.

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About the book
About the Author
Deep Learning with Python cover Grokking Deep Learning Cover Deep Learning with Pytorch cover Deep Learning and the Game of Go cover Deep Learning for Vision Systems cover Probabilistic Deep Learning cover
Deep Learning with Python Grokking Deep Learning Deep Learning with PyTorch Deep Learning and the Game of Go Deep Learning for Vision Systems Probabilistic Deep Learning
User Experience Level Intermediate Beginner Intermediate Intermediate Intermediate Experienced
Readers Who Want Deep learning from the ground up. Friendly illustrated tutorial on deep learning fundamentals Professional guide to image and text processing with PyTorch Apply deep learning by building a complete project Serious introduction to deep learning-based image processing Bayesian inference and probablistic programming for deep learning
Compatible with Python 3 Python 3 Python 3 Python 3 Python 3 Python 3
Special Features Written by Keras creator François Chollet Learn core deep learning algorithms using only high school mathematics. Includes an in-depth look at identifying anomalies in medical images Build a complete Go-playing bot that can challenge serious players A comprehensive look at deep learning for image recommendation and classification Create deep learning systems that return ranges of results based on probability
Praise "Chollet explains complex concepts with minimal fuss. A joy to read.” — Martin Görner, Google "From a masterful teacher who guides, illuminates, and encourages you along the way." — Kelvin D. Meeks, International Technology Ventures "We finally have a definitive treatise on PyTorch." — From the Foreword by Soumith Chintala, Co-creator of PyTorch "Inspired and inspiring. Highly recommended!" — Burk Hufnagel, Daugherty Business Solutions "Real-world problem solving without drowning you in details." — Burhan Ul Haq, Audit XPRT "Comprehensive walkthrough with lots of practical examples." — Diego Casella, Centrica Business Solutions, Belgium
Page Count 504 336 520 384 480 296

Product description

About the Author

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

Product details

  • Publisher ‏ : ‎ Manning; 2 edition (Dec 21 2021)
  • Language ‏ : ‎ English
  • Paperback ‏ : ‎ 504 pages
  • ISBN-10 ‏ : ‎ 1617296864
  • ISBN-13 ‏ : ‎ 978-1617296864
  • Item weight ‏ : ‎ 100 g
  • Dimensions ‏ : ‎ 18.73 x 3.56 x 23.5 cm
  • Customer Reviews:
    4.6 4.6 out of 5 stars 245 ratings

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Customer reviews

4.6 out of 5 stars
4.6 out of 5
245 global ratings

Top reviews from Canada

Reviewed in Canada 🇨🇦 on January 11, 2022
Reviewed in Canada 🇨🇦 on October 1, 2022
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3 people found this helpful
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Top reviews from other countries

Dr. A. R. Smith
3.0 out of 5 stars A walkthrough of his product and description of how it works without explanations
Reviewed in the United Kingdom 🇬🇧 on June 22, 2022
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5 people found this helpful
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John
2.0 out of 5 stars Very Cheap made
Reviewed in the United Kingdom 🇬🇧 on July 31, 2022
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Dimitrios FOTIADIS
5.0 out of 5 stars Excellent deep learning tutorial
Reviewed in the United Kingdom 🇬🇧 on January 24, 2023
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YOOMIN
5.0 out of 5 stars Book quality is excellent in condition
Reviewed in the United Kingdom 🇬🇧 on December 22, 2022
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Oscar
5.0 out of 5 stars Excelente libro
Reviewed in Mexico 🇲🇽 on May 5, 2022
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Oscar
5.0 out of 5 stars Excelente libro
Reviewed in Mexico 🇲🇽 on May 5, 2022
Es un libro excelente, el autor explica conceptos complicados de una forma sencilla y entendible. Realmente hizo un gran trabajo de pedagogo, además estás aprendiendo del mismísimo autor de Keras, el framework más popular para machine learning.

Eso sí, es importante tener conocimiento de programación y de conceptos matemáticos (cálculo, geometría, derivación, etc) ya que el Deep Learning es básicamente eso, pura matemática; vectores, matrices, operaciones vectoriales, espacios geométricos en varias dimensiones, etc. Cabe aclarar que el libro NO usa notaciones matemáticas; para darle sencillez, el autor decide usar en su lugar líneas de código que lo hacen mucho más digerible. Sin embargo, tener el conocimiento de estos conceptos te da el poder de entender lo que se está haciendo y de lo que se está hablando.

PD: el libro en físico incluye todas las versiones digitales! Incluso Kindle!
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2 people found this helpful
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