Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e, 3rd Edition by Aurelien Geron - ISBN: 9781098125974
Paperback
Unlock AI: Python, scikit-learn, Keras, TensorFlow, and practical machine learning.

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e, 3rd Edition

Concepts, Tools, and Techniques to Build Intelligent Systems

$128.96

  • Paperback

    850 pages

  • Release Date

    31 October 2022

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Summary

Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This best-selling book uses concrete examples, minimal theory, and production-ready Python frameworks–scikit-learn, Keras, and TensorFlow–to help you gain an intuitive understanding of the concepts and tools for building intelligent sys…

Book Details

ISBN-13:9781098125974
ISBN-10:1098125975
Author:Aurelien Geron
Publisher:O'Reilly Media
Imprint:O'Reilly Media
Format:Paperback
Number of Pages:850
Edition:3rd
Release Date:31 October 2022
Weight:666g
Dimensions:233mm x 178mm
About The Author

Aurelien Geron

Aurelien Geron is a Machine Learning consultant. A former Googler, he led YouTube’s 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, a telecom consulting firm. Before this he worked as an engineer in a variety of domains: finance (JP Morgan and Societe Generale), 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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