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Python Machine Learning - Second Edition: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow Paperback – September 20, 2017

4.4 out of 5 stars 155 ratings

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From the Publisher

Editorial Reviews

Review

"I bought the first version of this book, and now also the second. The new version is very comprehensive. If you are using Python - it's almost a reference. I also like the emphasis on neural networks (and TensorFlow) - which (in my view) is where the Python community is heading.

I am also planning to use this book in my teaching at Oxford University. The data pre-processing sections are also good. I found the sequence flow slightly unusual - but for an expert level audience, it's not a major issue."

--Ajit Jaokar, Data Science for IoT Course Creator and Lead Tutor at the University of Oxford / Principal Data Scientist

About the Author

Sebastian Raschka, author of the bestselling book, Python Machine Learning, has many years of experience with coding in Python, and he has given several seminars on the practical applications of data science, machine learning, and deep learning, including a machine learning tutorial at SciPy - the leading conference for scientific computing in Python.

While Sebastian's academic research projects are mainly centered around problem-solving in computational biology, he loves to write and talk about data science, machine learning, and Python in general, and he is motivated to help people develop data-driven solutions without necessarily requiring a machine learning background.

His work and contributions have recently been recognized by the departmental outstanding graduate student award 2016-2017, as well as the ACM Computing Reviews' Best of 2016 award. In his free time, Sebastian loves to contribute to open source projects, and the methods that he has implemented are now successfully used in machine learning competitions, such as Kaggle.

Vahid Mirjalili obtained his PhD in mechanical engineering working on novel methods for large-scale, computational simulations of molecular structures. Currently, he is focusing his research efforts on applications of machine learning in various computer vision projects at the Department of Computer Science and Engineering at Michigan State University.

Vahid picked Python as his number-one choice of programming language, and throughout his academic and research career he has gained tremendous experience with coding in Python. He taught Python programming to the engineering class at Michigan State University, which gave him a chance to help students understand different data structures and develop efficient code in Python.

While Vahid's broad research interests focus on deep learning and computer vision applications, he is especially interested in leveraging deep learning techniques to extend privacy in biometric data such as face images so that information is not revealed beyond what users intend to reveal. Furthermore, he also collaborates with a team of engineers working on self-driving cars, where he designs neural network models for the fusion of multispectral images for pedestrian detection.


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4.4 out of 5 stars
4.4 out of 5
155 customer ratings
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Reviewed in the United States on March 12, 2018
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Reviewed in the United States on September 25, 2017
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Top international reviews

Rob
1.0 out of 5 stars Do not buy and avoid Packt publications
Reviewed in the United Kingdom on January 9, 2020
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Peter
1.0 out of 5 stars Badly written basic applied stats book
Reviewed in the United Kingdom on October 5, 2019
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MJK-OK
4.0 out of 5 stars Useful material for those who know Python looking to get into ML
Reviewed in the United Kingdom on August 12, 2018
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Shuran Chen
5.0 out of 5 stars Well Design, great book for beginner
Reviewed in the United Kingdom on May 20, 2018
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Ammar
5.0 out of 5 stars Great reading for Udacity’s machine learning nanodegree
Reviewed in the United Kingdom on January 7, 2018
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VISA
5.0 out of 5 stars Great book! Presenting the machine learning algorithms and some ...
Reviewed in the United Kingdom on November 30, 2018
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Francesco
5.0 out of 5 stars One of the best
Reviewed in the United Kingdom on September 6, 2019
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Franco Arda
5.0 out of 5 stars Lots of explanations + code + math = awesome!
Reviewed in Germany on October 18, 2017
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Lúcio Flávio dos santos Rosa
5.0 out of 5 stars Five Stars
Reviewed in the United Kingdom on December 4, 2017
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Yannick Giovanakis
5.0 out of 5 stars Excellent learning for ML Beginners
Reviewed in Italy on February 15, 2018
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Nahida Parveen
5.0 out of 5 stars Must have. Highly recommended.
Reviewed in India on July 29, 2018
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Shreyas Chim
5.0 out of 5 stars The Best Python Machine Learning Book
Reviewed in India on September 12, 2019
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Mark
1.0 out of 5 stars Kindle app does not render this book. Don't even try
Reviewed in Australia on November 13, 2017
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Rajneesh W.
3.0 out of 5 stars Book Level: Intermediate readers
Reviewed in India on January 7, 2020
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GG
5.0 out of 5 stars I love this book. S U P E R!!
Reviewed in Italy on August 6, 2019
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