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Aurélien Géron

Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems Paperback – Illustrated, 15 October 2019

by Aurelien Geron (Author)

1,506 ratings

in Management Information Systems

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Through a series of recent 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 practical book shows you how.

By using concrete examples, minimal theory, and two production-ready Python frameworks-Scikit-Learn and TensorFlow-author Aurelien Geron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started.

Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets

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Product details

Publisher : Centre for Alternative Economic Policy Research; 2nd ed. edition (15 October 2019)
Language : English
Paperback : 600 pages
ISBN-10 : 1492032646
ISBN-13 : 978-1492032649
Dimensions : 17.78 x 3.05 x 23.37 cm

Best Sellers Rank: 100 in Books (See Top 100 in Books)
- 1 in Natural Language Processing
- 1 in Python Programming
- 1 in Computer Vision & Pattern Recognition

Customer Reviews:
1,506 ratings

Product description

About the Author

Aurélien Géron is a machine learning consultant and trainer. A former Googler, he led YouTube's video classification team from 2013 to 2016. He was also a founder and CTO of Wifirst (a leading Wireless ISP in France) from 2002 to 2012, and a founder and CTO of two consulting firms -- Polyconseil (telecom, media and strategy) and Kiwisoft (machine learning and data privacy).

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5 star		86%
4 star		9%
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2 star		1%
1 star		2%

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Stewart Menday

Well worth the money

Reviewed in Australia on 3 August 2020

Verified Purchase

This has to be one of the best hands-on machine learning books out there. If you have the 1st edition and thought it was good, I can highly recommend the 2nd. It is in full colour, has expanded content and most importantly has been updated for Tensorflow 2 and Keras (Tensorflow's preferred high level API). The only reason I didn't give it 5 stars and I have never given a book a 5 star review, is I thought it was lacking some practical detail around object detection and localisation, semantic segmentation and dealing with large datasets that don't fit into memory, those subjects are covered but not in a lot of detail and without code examples.

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Nirmani Ranchagoda

Great book

Reviewed in Australia on 27 August 2020

Verified Purchase

Book was well packced. This book has coloured images. It has codes to try on as well. Well instructed in a way such that even a beginner can follow. However my opinion is it is better to have a bit of python background before reading the book. I just finished only two chapters, I believe the rest of the chapters will also be good. Author explains theory and background in a very nice interesting manner. Love this book!

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G R Redshaw

fast path to productive ml

Reviewed in Australia on 18 August 2020

Verified Purchase

A book well written with practical, well explained examples. I've read a few ml books. This is one of my favourites.

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Davood Mosaddar

Very useful and user friendly

Reviewed in Australia on 11 September 2020

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Love this book. gets you started on the project right off the bat. highly recommend it.

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Ritesh Singh

This is a must have book for data scientists and AI programmers.

Reviewed in Australia on 21 October 2020

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This is a must-have book for AI programmers and data scientists.

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hemachandran

Awesome book for ML

Reviewed in Australia on 13 January 2021

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Good quality book and I’m still reading it thru..

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Riyaz

Good book for beginners!

Reviewed in Australia on 19 December 2020

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Very good book for beginner data science!!

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Amazon Customer

Amazing

Reviewed in Australia on 24 December 2019

Verified Purchase

Great book!

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Top reviews from other countries

aliparpar

Single handedly one of the best ML books on the market

Reviewed in the United Kingdom on 5 January 2020

Verified Purchase

If you have the budget to only buy one ML book, I would suggest going for this one. It covers most of the field in one book. Get a datacamo subscription too and you can break into the DS career.

9 people found this helpful

Steve Karmeinsky

Great intro to Machine Learning

Reviewed in the United Kingdom on 5 March 2020

Verified Purchase

I'm currently on a course learning Machine Learning and family and this book was recommended (well earlier revision), but it explains things well with good examples.

I ordered on Kindle as much prefer reading that way

Recommended if new to ML/DL/NN etc

4 people found this helpful

Panos

Highly recommended

Reviewed in the United Kingdom on 10 February 2020

Verified Purchase

This book was just released, and I'm only a few chapters into it, but I can already attest that it's an excellent approach to the topic. It reads like the book I would have written (or perhaps would have liked to have written) if I were to pen a volume on artificial intelligence. It's a long-overdue addition to the subject, and I'm thrilled to see it executed so well.

4 people found this helpful

LEIGH ZHAO

Book Review

Reviewed in the United Kingdom on 30 July 2020

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It’s a colored book. Very well written with self-containing chapters, so you could either read from cover to cover or jump to the chapters most useful for you. Great for a wide knowledge range, either you don‘t know much about machine learning yet - this book would be a good starting point, or if you look for customize layers in neural networks, this book also talks about how to do that with subclassing Keras layers. It also mentions relevant papers for further reading.

2 people found this helpful

macunix

Very good book on machine learning and deep learning

Reviewed in the United Kingdom on 28 August 2020

Verified Purchase

Good book about the machine learning and deep learning. with pratical codes using sklearn, tf2.0. but it is not easy to form a complete solution just from this book. It is worthy read a few times on some chapters to understand better. wonder any alternatives or complementary books...

One person found this helpful

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