Python Machine Learning - Secon - Sebastian Raschka,Vahid Mirjali.pdf

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Python Machine Learning
Second Edition
Machine Learning and Deep Learning with Python,
scikit-learn, and TensorFlow
Sebastian Raschka
Vahid Mirjalili
BIRMINGHAM - MUMBAI
Python Machine Learning
Second Edition
Copyright © 2017 Packt Publishing
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However, Packt Publishing cannot guarantee the accuracy of this information.
First published: September 2015
Second edition: September 2017
Production reference: 2150917
Published by Packt Publishing Ltd.
Livery Place
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Birmingham B3 2PB, UK.
ISBN 978-1-78712-593-3
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Credits
Authors
Sebastian Raschka
Vahid Mirjalili
Proofreader
Reviewers
Jared Huffman
Huai-En, Sun (Ryan Sun)
Acquisition Editor
Frank Pohlmann
Content Development Editor
Chris Nelson
Project Editor
Monika Sangwan
Technical Editors
Bhagyashree Rai
Nidhisha Shetty
Copy Editor
Safis Editing
Indexer
Tejal Daruwale Soni
Graphics
Kirk D'Penha
Production Coordinator
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Safis Editing
Project Coordinator
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About the Authors
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.
I would like to take this opportunity to thank the great Python
community and developers of open source packages who helped
me create the perfect environment for scientific research and data
science. Also, I want to thank my parents who always encouraged
and supported me in pursuing the path and career that I was so
passionate about.
Special thanks to the core developers of scikit-learn. As a contributor
to this project, I had the pleasure to work with great people who are
not only very knowledgeable when it comes to machine learning but
are also excellent programmers. Lastly, I'd like to thank Elie Kawerk,
who volunteered to review the book and provided valuable feedback
on the new chapters.
Sebastian Raschka
, the author of the bestselling book,
Python Machine Learning,

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