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  • Deep Learning with Python, Second Edition
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Customer reviews

4.6 out of 5 stars
4.6 out of 5
241 global ratings
5 star
82%
4 star
9%
3 star
3%
2 star
2%
1 star
4%
Deep Learning with Python, Second Edition

Deep Learning with Python, Second Edition

byFrancois Chollet
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From Canada

Kee
5.0 out of 5 stars Deep Learning for a programmer
Reviewed in Canada 🇨🇦 on January 11, 2022
This book provides a good introduction for programmers that are interested in the subject.
As the author is kind to leave complex math aside while explaining the concept.
This book is a great addition to a programmer's library.
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Usman Ahmed
1.0 out of 5 stars Book is good; seller is not
Reviewed in Canada 🇨🇦 on October 1, 2022
Verified Purchase
The contents of the book are great but the seller doesn't provide code for online access, which according to the first page of the book, should be there. Not sure if this seller is authorized to sell this book.
3 people found this helpful
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From other countries

Fabrice J.
5.0 out of 5 stars Livré exactement dans le délai prévu et neuf
Reviewed in France 🇫🇷 on March 8, 2023
Verified Purchase
Rien à dire: le colis est arrivé en temps et en heure. Le livre est neuf et est conforme à la commande passée.
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Daniel Martinez
5.0 out of 5 stars Un básico
Reviewed in Mexico 🇲🇽 on January 24, 2023
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El libro es original, lo pude registrar sin problemas en la dirección web y el contenido es excelente.
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Fabrizio C.
5.0 out of 5 stars Utilissimo
Reviewed in Italy 🇮🇹 on August 21, 2022
Verified Purchase
Uno dei migliori libri in commercio di macchine learning, in particolare sul deep learning usando python e tensor flow.
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editronikx
5.0 out of 5 stars Buen libro
Reviewed in the United States 🇺🇸 on May 21, 2023
Verified Purchase
Libro en inglés pero buen contenido
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Seyedpedram
5.0 out of 5 stars Top
Reviewed in Germany 🇩🇪 on February 4, 2023
Verified Purchase
The quality of the book itself is really good. I also love the content.
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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
Verified Purchase
Deep learning tutorial, excellently balanced between hands-on examples and deeper concepts explained in an intuitive, non-mathematical way. Very well structured chapters explain step by step the workflow for framing, developing and deploying a real world model. Easy to follow, uses informal language, but with great depth. Highly recommended.
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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
Verified Purchase
Delivered wrapped with vynil cover and good vivid colours in content
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Brett
5.0 out of 5 stars Introductory tour with unmatched insights from a giant in the field
Reviewed in the United States 🇺🇸 on February 3, 2022
Verified Purchase
This book is ideally suited to people who want a meaningful introduction into the most important contemporary concepts in Deep Learning. The book is accessible to people who lack both programming and linear algebra. Neither are needed to get a full understanding of everything the book offers.

IMO, the greatest moments in the book are the asides that appear in every chapter. The author will take a paragraph to note in passing things like '... no one really knows for sure why batch normalization helps. There are various hypotheses, but no certitudes." Or, "Importantly, I would generally recommend placing the previous layer's activation after the batch normalization layer (although this is still a subject of debate)." There is even an entire chapter dedicated to musings on the future of Deep Learning and general AI. This is the cherry on top that you don't get with most offers. Chollet offers them in nearly every chapter.

The book may as well have been called "Deep Learning with Keras" and that's not a bad thing. All the code is freely downloadable and can be run for free on a Google platform. You can freely ignore the implementation details and Python and simply run and learn from the notebooks provided. NOTE: As of February 2022, the new M1 Macs have bugs in the implementation of tensorflow that prevent a few code samples from working correctly. AND, some examples take so long to run (many hours) that there may be issues running them at Google. Frustrating though it might be, it does not detract from the experience.

As to cons, I don't see enough to warrant taking a star off the review. All important concepts are covered at an introductory level. The code works. The writing is clear. The author is an expert. There is a bizarre convention of having diagrams flow from the bottom to the top instead of top-down.

It's a good intro and basic reference. You'll get into more depth by taking the OpenAI courses at Coursera, but I'd actually recommend those as a next step after fully absorbing this book. Recommended.

While the book is titled "Deep Learning with Python", it might have been better titled, "Deep Learning with Keras." While Python is ostensibly
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