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Practical Data Science with­ Hadoop and Spark
Designing and Building Effective Analytics at Scale

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Format
Electronic Book Text, 256 pages
Other Formats Available

Paperback : £32.54

Published
United States, 8 December 2016

This book provides a unique perspective on applying data science with Hadoop by explaining what data science with Hadoop is all about, its practical business applications, and then diving deep into the details and providing a hands-on tutorial and showcase of various use-cases from the real world. The authors bring together all the practical knowledge students will need to do real, useful data science with Hadoop.

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Product Description

This book provides a unique perspective on applying data science with Hadoop by explaining what data science with Hadoop is all about, its practical business applications, and then diving deep into the details and providing a hands-on tutorial and showcase of various use-cases from the real world. The authors bring together all the practical knowledge students will need to do real, useful data science with Hadoop.

The full text downloaded to your computer

With eBooks you can:

eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps.

Upon purchase, you'll gain instant access to this eBook.

Time limit

The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed.

Show more
Product Details
EAN
9780134029726
ISBN
0134029720
Publisher
Age Range

Table of Contents

  • Part I: Data Science with Hadoop—An Overview
  • Chapter 1: Introduction to Data Science
  • Chapter 2: Use Cases for Data Science
  • Chapter 3: Hadoop and Data Science
  • Part II: Preparing and Visualizing Data with Hadoop
  • Chapter 4: Getting Data into Hadoop
  • Chapter 5: Data Munging with Hadoop
  • Chapter 6: Exploring and Visualizing Data
  • Part III: Applying Data Modeling with Hadoop
  • Chapter 7: Machine Learning with Hadoop
  • Chapter 8: Predictive Modeling
  • Chapter 9: Clustering
  • Chapter 10: Anomaly Detection with Hadoop
  • Chapter 11: Natural Language Processing
  • Chapter 12: Data Science with Hadoop—The Next Frontier
  • Appendix A: Book Web Page and Code Download
  • Appendix B: HDFS Quick Start
  • Appendix C: Additional Background on Data Science and Apache Hadoop and Spark

About the Author

Ofer Mendelevitch is Vice President of Data Science at Lendup, where he is responsible for Lendup’s machine learning and advanced analytics group. Prior to joining Lendup, Ofer was Director of Data Science at Hortonworks, where he was responsible for helping Hortonwork’s customers apply Data Science with Hadoop and Spark to big data across various industries including healthcare, finance, retail and others. Before Hortonworks, Ofer served as Entrepreneur in Residence at XSeed Capital, VP of Engineering at Nor1, and Director of Engineering at Yahoo!.

 

Casey Stella is a Principal Software Engineer focusing on Data Science at Hortonworks, which provides an open source Hadoop distribution. Casey’s primary responsibility is leading the analytics/data science team for the Apache Metron (Incubating) Project, an open source cybersecurity project. Prior to Hortonworks, Casey was an architect at Explorys, which was a medical informatics startup spun out of the Cleveland Clinic.  In the more distant past, Casey served as a developer at Oracle, Research Geophysicist at ION Geophysical and as a poor graduate student in Mathematics at Texas A&M.

 

Douglas Eadline, PhD, began his career as analytical chemist with an interest in computer methods. Starting with the first Beowulf how-to document, Doug has written hundreds of articles, white papers, and instructional documents covering many aspects of HPC and Hadoop computing. Prior to starting and editing the popular ClusterMonkey.net website in 2005, he served as editor¿in¿chief for ClusterWorld Magazine and was senior HPC editor for Linux Magazine. He has practical hands-on experience in many aspects of HPC and Apache Hadoop, including hardware and software design, benchmarking, storage, GPU, cloud computing, and parallel computing. Currently, he is a writer and consultant to the HPC/analytics industry and leader of the Limulus Personal Cluster Project (http://limulus.basement-supercomputing.com). He is author of the Apache Hadoop® Fundamentals LiveLessons and Apache Hadoop® YARN Fundamentals LiveLessons videos from Pearson, and is book co-author of Apache Hadoop® YARN: Moving beyond MapReduce and Batch Processing with Apache Hadoop 2 and author of Hadoop® 2 Quick Start Guide: Learn the Essentials of Big Data Computing in the Apache Hadoop 2 Ecosystem, also from Addison-Wesley, and is author of High Performance Computing for Dummies.

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