Advanced Machine Learning with Python PDF
Preview Advanced Machine Learning with Python
Advanced Machine Learning with Python Solve challenging data science problems by mastering cutting-edge machine learning techniques in Python John Hearty BIRMINGHAM - MUMBAI Advanced Machine Learning with Python Copyright © 2016 Packt Publishing All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews. Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book. Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information. First published: July 2016 Production reference: 1220716 Published by Packt Publishing Ltd. Livery Place 35 Livery Street Birmingham B3 2PB, UK. ISBN 978-1-78439-863-7 www.packtpub.com [ FM-2 ] Credits Author Project Coordinator John Hearty Nidhi Joshi Reviewers Proofreader Jared Huffman Safis Editing Ashwin Pajankar Indexer Mariammal Chettiyar Commissioning Editor Akram Hussain Graphics Disha Haria Acquisition Editor Sonali Vernekar Production Coordinator Arvindkumar Gupta Content Development Editor Mayur Pawanikar Cover Work Arvindkumar Gupta Technical Editor Suwarna Patil Copy Editor Tasneem Fatehi [ FM-3 ] About the Author John Hearty is a consultant in digital industries with substantial expertise in data science and infrastructure engineering. Having started out in mobile gaming, he was drawn to the challenge of AAA console analytics. Keen to start putting advanced machine learning techniques into practice, he signed on with Microsoft to develop player modelling capabilities and big data infrastructure at an Xbox studio. His team made significant strides in engineering and data science that were replicated across Microsoft Studios. Some of the more rewarding initiatives he led included player skill modelling in asymmetrical games, and the creation of player segmentation models for individualized game experiences. Eventually John struck out on his own as a consultant offering comprehensive infrastructure and analytics solutions for international client teams seeking new insights or data-driven capabilities. His favourite current engagement involves creating predictive models and quantifying the importance of user connections for a popular social network. After years spent working with data, John is largely unable to stop asking questions. In his own time, he routinely builds ML solutions in Python to fulfil a broad set of personal interests. These include a novel variant on the StyleNet computational creativity algorithm and solutions for algo-trading and geolocation-based recommendation. He currently lives in the UK. [ FM-4 ] About the Reviewers Jared Huffman is a lifelong gamer and extreme data geek. After completing his bachelor's degree in computer science, he started his career in his hometown of Melbourne, Florida. While there, he honed his software development skills, including work on a credit card-processing system and a variety of web tools. He finished it off with a fun contract working at NASA's Kennedy Space Center before migrating to his current home in the Seattle area. Diving head first into the world of data, he took up a role working on Microsoft's internal finance tools and reporting systems. Feeling that he could no longer resist his love for video games, he joined the Xbox division to build their Business. To date, Jared has helped ship and support 12 games and presented at several events on various machine learning and other data topics. His latest endeavor has him applying both his software skills and analytics expertise in leading the data science efforts for Minecraft. There he gets to apply machine learning techniques, trying out fun and impactful projects, such as customer segmentation models, churn prediction, and recommendation systems. Outside of work, Jared spends much of his free time playing board games and video games with his family and friends, as well as dabbling in occasional game development. First I'd like to give a big thanks to John for giving me the honor of reviewing this book; it's been a great learning experience. Second, thanks to my amazing wife, Kalen, for allowing me to repeatedly skip chores to work on it. Last, and certainly not least, I'd like to thank God for providing me the opportunities to work on things I love and still make a living doing it. Being able to wake up every day and create games that bring joy to millions of players is truly a pleasure. [ FM-5 ] Ashwin Pajankar is a software professional and IoT enthusiast with more than 8 years of experience in software design, development, testing, and automation. He graduated from IIIT Hyderabad, earning an M. Tech in computer science and engineering. He holds multiple professional certifications from Oracle, IBM, Teradata, and ISTQB in development, databases, and testing. He has won several awards in college through outreach initiatives, at work for technical achievements, and community service through corporate social responsibility programs. He was introduced to Raspberry Pi while organizing a hackathon at his workplace, and has been hooked on Pi ever since. He writes plenty of code in C, Bash, Python, and Java on his cluster of Pis. He's already authored two books on Raspberry Pi and reviewed three other titles related to Python for Packt Publishing. His LinkedIn Profile is https://in.linkedin.com/in/ashwinpajankar. I would like to thank my wife, Kavitha, for the motivation. [ FM-6 ] www.PacktPub.com eBooks, discount offers, and more Did you know that Packt offers eBook versions of every book published, with PDF and ePub files available? You can upgrade to the eBook version at www.PacktPub.com and as a print book customer, you are entitled to a discount on the eBook copy. Get in touch with us at [email protected] for more details. At www.PacktPub.com, you can also read a collection of free technical articles, sign up for a range of free newsletters and receive exclusive discounts and offers on Packt books and eBooks. TM https://www2.packtpub.com/books/subscription/packtlib Do you need instant solutions to your IT questions? PacktLib is Packt's online digital book library. Here, you can search, access, and read Packt's entire library of books. Why subscribe? • Fully searchable across every book published by Packt • Copy and paste, print, and bookmark content • On demand and accessible via a web browser [ FM-7 ] Of the many people I feel gratitude towards, I particularly want to thank my parents … mostly for their patience. I'd like to extend thanks to Tyler Lowe for his invaluable friendship, to Mark Huntley for his bothersome emphasis on accuracy, and to the former team at Lionhead Studios. I also greatly value the excellent work done by Jared Huffman and the industrious editorial team at Packt Publishing, who were hugely positive and supportive throughout the creation of this book. Finally, I'd like to dedicate the work and words herein to you, the reader. There has never been a better time to get to grips with the subjects of this book; the world is stuffed with new opportunities that can be seized using creativity and an appropriate model. I hope for your every success in the pursuit of those solutions. [ FM-9 ]
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