Large Scale Machine Learning with Python.pdf

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Large Scale Machine Learning
with Python
Learn to build powerful machine learning models
quickly and deploy large-scale predictive applications
Bastiaan Sjardin
Luca Massaron
Alberto Boschetti
BIRMINGHAM - MUMBAI
Large Scale Machine Learning with Python
Copyright © 2016 Packt Publishing
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However, Packt Publishing cannot guarantee the accuracy of this information.
First published: July 2016
Production reference: 1270716
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham B3 2PB, UK.
ISBN 978-1-78588-721-5
www.packtpub.com
Credits
Authors
Bastiaan Sjardin
Luca Massaron
Alberto Boschetti
Reviewers
Oleg Okun
Kai Londenberg
Commissioning Editor
Akram Hussain
Acquisition Editor
Sonali Vernekar
Content Development Editor
Sumeet Sawant
Technical Editor
Manthan Raja
Copy Editor
Tasneem Fatehi
Proofreader
Safis Editing
Indexer
Mariammal Chettiyar
Graphics
Disha Haria
Kirk D'Penha
Production Coordinator
Arvindkumar Gupta
Cover Work
Arvindkumar Gupta
Project Coordinator
Shweta H Birwatkar
About the Authors
intelligence and mathematics. He has a MSc degree in cognitive science obtained
at the University of Leiden together with on campus courses at Massachusetts
Institute of Technology (MIT). In the past 5 years, he has worked on a wide range
of data science and artificial intelligence projects. He is a frequent community TA
at Coursera in the social network analysis course from the University of Michigan
and the practical machine learning course from Johns Hopkins University. His
programming languages of choice are Python and R. Currently, he is the cofounder
of Quandbee (
http://www.quandbee.com/
), a company providing machine learning
and artificial intelligence applications at scale.
Bastiaan Sjardin
is a data scientist and founder with a background in artificial
Luca Massaron
is a data scientist and marketing research director who is
specialized in multivariate statistical analysis, machine learning, and customer
insight, with over a decade of experience in solving real-world problems and
generating value for stakeholders by applying reasoning, statistics, data mining,
and algorithms. From being a pioneer of Web audience analysis in Italy to achieving
the rank of a top ten Kaggler, he has always been very passionate about everything
regarding data and its analysis, and also about demonstrating the potential of data-
driven knowledge discovery to both experts and non-experts. Favoring simplicity
over unnecessary sophistication, he believes that a lot can be achieved in data science
just by doing the essentials.
I would like to thank Yukiko and Amelia for their continued
support, help, and loving patience.

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