- Reading level: 10+ years
- Paperback: 568 pages
- Publisher: Shroff/O'Reilly; First edition (2017)
- Language: English
- ISBN-10: 9789352135219
- ISBN-13: 978-9352135219
- ASIN: 9352135210
- Product Dimensions: 22.9 x 17.8 x 2.6 cm
- Average Customer Review: 55 customer reviews
- Amazon Bestsellers Rank: #1,467 in Books (See Top 100 in Books)
Hands-On Machine Learning with Scikit-Learn and Tensor Flow: Concepts, Tools, and Techniques to Build Intelligent Systems Paperback – 2017
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About the Author
AurÈlien GÈron is a Machine Learning consultant. A former Googler, he led the YouTube video classification team from 2013 to 2016. He was also a founder and CTO of Wifirst from 2002 to 2012, a leading Wireless ISP in France and a founder and CTO of Polyconseil in 2001, the firm that now manages the electric car sharing service Autolib'.Before this he worked as an engineer in a variety of domains: finance (JP Morgan and SociÈtÈ GÈnÈrale), defense (Canada's DOD) and healthcare (blood transfusion). He published a few technical books (on C++, WiFi and Internet architectures) and was a Computer Science lecturer in a French engineering school.A few fun facts: he taught his 3 children to count in binary with their fingers (up to 1023), he studied microbiology and evolutionary genetics before going into software engineering and his parachute didn't open on the 2nd jump.
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This is one of the best books you can get for someone who is just starting out in ML, in its libraries such as Tensorflow, It covers the basics very good. As a book, it is 5/5
Once you are done with this book, the ideal next step is the "Deep Learning Book By Ian Goodfellow".
Sadly my copy didn't look so good, If it were an under 300 book, I would have let it slide but when the book costs 1450 (Which it is totally worth it) I expected a much better copy.
Quite simply written and not intimidating at all. For those looking for a very deep look into the basics and the math background of the concepts should probably check out Duke University’s machine learning mastery with excel - which is a rigorous crash course on the very basics of the math.
The problem with book quality on amazon is hit or miss. Paper that it’s published on is slightly cheap quality.
Looks like also someone has used the book. That may be a concern to some people.
At the same time I was unable to find a book dedicated on deep learning with tensorflow. Not a bad book at all, but incompatible with latest version of tensorflow. Can be used as a reference for learning/ understanding cnns, rnn etc.