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Pentreath - Machine learning with Spark: create scalable machine learning applications to power a modern data-driven business using Spark

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Pentreath Machine learning with Spark: create scalable machine learning applications to power a modern data-driven business using Spark
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Machine learning with Spark: create scalable machine learning applications to power a modern data-driven business using Spark: summary, description and annotation

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Getting up and running with Spark -- Designing a machine learning system -- Obtaining, processing, and preparing data with Spark -- Building a recommendation engine with Spark -- Building a classification model with Spark -- Building a regression model with Spark -- Building a clustering model with Spark -- Dimensionality reduction with Spark -- Advanced text processing with Spark -- Real-time machine learning with Spark streaming

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Machine Learning with Spark

Machine Learning with Spark

Copyright 2015 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: February 2015

Production reference: 1170215

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham B3 2PB, UK.

ISBN 978-1-78328-851-9

www.packtpub.com

Cover image by Akshay Paunikar (<>)

Credits

Author

Nick Pentreath

Reviewers

Andrea Mostosi

Hao Ren

Krishna Sankar

Commissioning Editor

Rebecca You

Acquisition Editor

Rebecca You

Content Development Editor

Susmita Sabat

Technical Editors

Vivek Arora

Pankaj Kadam

Copy Editor

Karuna Narayanan

Project Coordinator

Milton Dsouza

Proofreaders

Simran Bhogal

Maria Gould

Ameesha Green

Paul Hindle

Indexer

Priya Sane

Graphics

Sheetal Aute

Abhinash Sahu

Production Coordinator

Nitesh Thakur

Cover Work

Nitesh Thakur

About the Author

Nick Pentreath has a background in financial markets, machine learning, and software development. He has worked at Goldman Sachs Group, Inc.; as a research scientist at the online ad targeting start-up Cognitive Match Limited, London; and led the Data Science and Analytics team at Mxit, Africa's largest social network.

He is a cofounder of Graphflow, a big data and machine learning company focused on user-centric recommendations and customer intelligence. He is passionate about combining commercial focus with machine learning and cutting-edge technology to build intelligent systems that learn from data to add value to the bottom line.

Nick is a member of the Apache Spark Project Management Committee.

Acknowledgments

Writing this book has been quite a rollercoaster ride over the past year, with many ups and downs, late nights, and working weekends. It has also been extremely rewarding to combine my passion for machine learning with my love of the Apache Spark project, and I hope to bring some of this out in this book.

I would like to thank the Packt Publishing team for all their assistance throughout the writing and editing process: Rebecca, Susmita, Sudhir, Amey, Neil, Vivek, Pankaj, and everyone who worked on the book.

Thanks also go to Debora Donato at StumbleUpon for assistance with data- and legal-related queries.

Writing a book like this can be a somewhat lonely process, so it is incredibly helpful to get the feedback of reviewers to understand whether one is headed in the right direction (and what course adjustments need to be made). I'm deeply grateful to Andrea Mostosi, Hao Ren, and Krishna Sankar for taking the time to provide such detailed and critical feedback.

I could not have gotten through this project without the unwavering support of all my family and friends, especially my wonderful wife, Tammy, who will be glad to have me back in the evenings and on weekends once again. Thank you all!

Finally, thanks to all of you reading this; I hope you find it useful!

About the Reviewers

Andrea Mostosi is a technology enthusiast. An innovation lover since he was a child, he started a professional job in 2003 and worked on several projects, playing almost every role in the computer science environment. He is currently the CTO at The Fool, a company that tries to make sense of web and social data. During his free time, he likes traveling, running, cooking, biking, and coding.

I would like to thank my geek friends: Simone M, Daniele V, Luca T, Luigi P, Michele N, Luca O, Luca B, Diego C, and Fabio B. They are the smartest people I know, and comparing myself with them has always pushed me to be better.

Hao Ren is a software developer who is passionate about Scala, distributed systems, machine learning, and Apache Spark. He was an exchange student at EPFL when he learned about Scala in 2012. He is currently working in Paris as a backend and data engineer for ClaraVistaa company that focuses on high-performance marketing. His work responsibility is to build a Spark-based platform for purchase prediction and a new recommender system.

Besides programming, he enjoys running, swimming, and playing basketball and badminton. You can learn more at his blog http://www.invkrh.me.

Krishna Sankar is a chief data scientist at BlackArrow, where he is focusing on enhancing user experience via inference, intelligence, and interfaces. Earlier stints include working as a principal architect and data scientist at Tata America International Corporation, director of data science at a bioinformatics start-up company, and as a distinguished engineer at Cisco Systems, Inc. He has spoken at various conferences about data science (http://goo.gl/9pyJMH), machine learning (http://goo.gl/sSem2Y), and social media analysis (http://goo.gl/D9YpVQ). He has also been a guest lecturer at the Naval Postgraduate School. He has written a few books on Java, wireless LAN security, Web 2.0, and now on Spark. His other passion is LEGO robotics. Earlier in April, he was at the St. Louis FLL World Competition as a robots design judge.

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