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Karim M.R. - Large Scale Machine Learning with Spark

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Karim M.R. Large Scale Machine Learning with Spark
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Discover everything you need to build robust machine learning applications with Spark 2.0 About This Book Get the most up-to-date book on the market that focuses on design, engineering, and scalable solutions in machine learning with Spark 2.0.0 Use Sparks machine learning library in a big data environment You will learn how to develop high-value applications at scale with ease and a develop a personalized design Who This Book Is For This book is for data science engineers and scientists who work with large and complex data sets. You should be familiar with the basics of machine learning concepts, statistics, and computational mathematics. Knowledge of Scala and Java is advisable. What You Will Learn Get solid theoretical understandings of ML algorithms Configure Spark on cluster and cloud infrastructure to develop applications using Scala, Java, Python, and R Scale up ML applications on large cluster or cloud infrastructures Use Spark ML and MLlib to develop ML pipelines with recommendation system, classification, regression, clustering, sentiment analysis, and dimensionality reduction Handle large texts for developing ML applications with strong focus on feature engineering Use Spark Streaming to develop ML applications for real-time streaming Tune ML models with cross-validation, hyperparameters tuning and train split Enhance ML models to make them adaptable for new data in dynamic and incremental environments In Detail Data processing, implementing related algorithms, tuning, scaling up and finally deploying are some crucial steps in the process of optimising any application. Spark is capable of handling large-scale batch and streaming data to figure out when to cache data in memory and processing them up to 100 times faster than Hadoop-based MapReduce. This means predictive analytics can be applied to streaming and batch to develop complete machine learning (ML) applications a lot quicker, making Spark an ideal candidate for large data-intensive applications. This book focuses on design engineering and scalable solutions using ML with Spark. First, you will learn how to install Spark with all new features from the latest Spark 2.0 release. Moving on, youll explore important concepts such as advanced feature engineering with RDD and Datasets. After studying developing and deploying applications, you will see how to use external libraries with Spark. In summary, you will be able to develop complete and personalised ML applications from data collections, model building, tuning, and scaling up to deploying on a cluster or the cloud. Style and approach This book takes a practical approach where all the topics explained are demonstrated with the help of real-world use cases.

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Large Scale Machine Learning with Spark

Table of Contents
Large Scale Machine Learning with Spark

Large Scale Machine Learning with Spark

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 authors, 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: October 2016

Production reference: 1201016

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham

B3 2PB, UK.

ISBN 978-1-78588-874-8

www.packtpub.com

Credits

Authors

Md. Rezaul Karim

Md. Mahedi Kaysar

Copy Editor

Safis Editing

Reviewer

Muthukumar Subramanian

Project Coordinator

Shweta H Birwatkar

Commissioning Editor

Akram Hussain

Proofreader

Safis Editing

Acquisition Editor

Lester Frias

Indexer

Aishwarya Gangawane

Content Development Editor

Amrita Noronha

Graphics

Disha Haria

Technical Editor

Akash Patel

Production Coordinator

Arvindkumar Gupta

About the Authors

Md. Rezaul Karim has more than 8 years of experience in the area of research and development with a solid knowledge of algorithms and data structures, focusing C, C++, Java, R, and Python and big data technologies such as Spark, Kafka, DC/OS, Docker, Mesos, Hadoop, and MapReduce.

He was first enchanted by machine learning while studying an Advanced Artificial Intelligence post-graduate course by applying the combined technique of Hadoop-based MapReduce and machine learning together for market basket analysis on large-scale business-oriented transactional databases in back 2010. Consequently, his research interests include machine learning, data mining, Semantic Web, big data, and bioinformatics. He has published more than 30 research papers in renowned peer-reviewed international journals and conferences focusing on the areas of data mining, machine learning, and bioinformatics, with good citations.

He is a Software Engineer and Researcher currently working at the Insight Centre for Data Analytics, Ireland (the largest data analytics center in Ireland and the largest Semantic Web research institute in the world) as a PhD Researcher. He is also a PhD candidate at the National University of Ireland, Galway. He also holds an ME (Master of Engineering) degree in Computer Engineering from the Kyung Hee University, Korea, majoring in data mining and knowledge discovery. And he has a BS (Bachelor of Science) degree in Computer Science from the University of Dhaka, Bangladesh.

Before joining the Insight Center for Data Analytics, he had been working as a Lead Software Engineer with Samsung Electronics, where he worked with the distributed Samsung R&D centers across the world, including Korea, India, Vietnam, Turkey, UAE, Brazil, and Bangladesh. Before that, he worked as a Graduate Research Assistant in the Database Lab at Kyung Hee University, Korea, while working towards his Master's degree. He also worked as an R&D Engineer with BMTech21 Worldwide, Korea. Even before that, he worked as a Software Engineer with i2SoftTechnology, Dhaka, Bangladesh.

This book could not have been written without the support of my family and friends. In particular, my wife Saroar and my son Shadman deserve many thanks for their patience and encouragement throughout the past year.

I would like to give special thanks to Md. Mahedi Kaysar for co-authoring this book, and without his contributions, the writing would have been impossible. I would also like to thank Jaynal Abedin for his valuable suggestions towards different statistical and machine algorithms.Overall, I would like to dedicate this book to my respected teacher and research Guru Prof. Dr. Chowdhury Farhan Ahmed (Dept. of Computer Science & Engineering, University of Dhaka, Bangladesh) for his endless contributions to my life.

Further, I would like to thank the acquisition, content development and technical editors of Packt Publishing (and others who were involved to this book title) for their sincere cooperation and coordination. Additionally, without the work of numerous researchers who shared their expertise in publications, lectures, and source code, this book might not exist at all! Finally, I appreciate the efforts of the Apache Spark community and all those who have contributed to Spark APIs, whose work ultimately brought the machine learning to the masses.

Md. Mahedi Kaysar is a Software Engineer and Researcher at the Insight Center for Data Analytics (the largest data analytics center across the Ireland and the largest semantic web research institute in the world), Dublin City University (DCU), Ireland. Before joining the Insight Center at DCU, he worked as a Software Engineer at the Insight Center for Data Analytics, National University of Ireland, Galway and Samsung Electronics, Bangladesh.

He has more than 5 years of experience in research and development with a strong background in algorithms and data structures concentrating on C, Java, Scala, and Python. He has lots of experience in enterprise application development and big data analytics.

He obtained a BSc in Computer Science and Engineering from the Chittagong University of Engineering and Technology, Bangladesh. Now, he has started his postgraduate research in Distributed and Parallel Computing at the Dublin City University, Ireland.

His research interests include Distributed Computing, Semantic Web, Linked Data, big data, Internet of Everything, and machine learning. Moreover, he was involved in a research project in collaboration with CISCO Systems Inc. in the area of Internet of Everything and Semantic Web Technologies. His duties were to develop an IoT-enabled meeting management system, a scalable system for stream processing, designing, and showcasing the use cases of a project.

This book could not have been written without the support of my family and friends. In particular, my beloved wife IrinAkhtar deserves many thanks for her patience and encouragement throughout the past year.

I would like to give special thanks to Md. Rezaul Karim for co-authoring this book and without his contributions, the writing would have been impossible. I would also like thank Packt Publishing and the group members who provides us a lot of support with the writing of this book, which helped to complete the book in time.

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