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Java for Data Science

You're reading from Java for Data Science

Product type Book

Published in Jan 2017

Publisher Packt

ISBN-13 9781785280115

Pages 386 pages

Edition 1st Edition

Languages

Concepts

Authors (2):

Richard M. Reese

Jennifer L. Reese

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Table of Contents (19) Chapters

Java for Data Science

Credits

About the Authors

About the Reviewers

www.PacktPub.com

Customer Feedback

Preface

Getting Started with Data Science

Data Acquisition

Data Cleaning

Data Visualization

Statistical Data Analysis Techniques

Machine Learning

Neural Networks

Deep Learning

Text Analysis

Visual and Audio Analysis

Mathematical and Parallel Techniques for Data Analysis

Bringing It All Together

Using map-reduce

Map-reduce is a model for processing large sets of data in a parallel, distributed manner. This model consists of a map method for filtering and sorting data, and a reduce method for summarizing data. The map-reduce framework is effective because it distributes the processing of a dataset across multiple servers, performing mapping and reduction simultaneously on smaller pieces of the data. Map-reduce provides significant performance improvements when implemented in a multi-threaded manner. In this section, we will demonstrate a technique using Apache's Hadoop implementation. In the Using Java 8 to perform map-reduce section, we will discuss techniques for performing map-reduce using Java 8 streams.

Hadoop is a software ecosystem providing support for parallel computing. Map-reduce jobs can be run on Hadoop servers, generally set up as clusters, to significantly improve processing speeds. Hadoop has trackers that run map-reduce operations on nodes within a Hadoop cluster...

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Authors (2)

Richard M. Reese

Richard Reese has worked in the industry and academics for the past 29 years. For 10 years he provided software development support at Lockheed and at one point developed a C based network application. He was a contract instructor providing software training to industry for 5 years. Richard is currently an Associate Professor at Tarleton State University in Stephenville Texas. Richard is the author of various books and video courses some of which are as follows: Natural Language Processing with Java. Java for Data Science Getting Started with Natural Language Processing in Java

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Jennifer L. Reese

Jennifer L. Reese studied computer science at Tarleton State University. She also earned her M.Ed. from Tarleton in December 2016. She currently teaches computer science to high-school students. Her interests include the integration of computer science concepts with other academic disciplines, increasing diversity in computer science courses, and the application of data science to the field of education. She has co-authored two books: Java for Data Science and Java 7 New Features Cookbook. She previously worked as a software engineer. In her free time she enjoys reading, cooking, and traveling—especially to any destination with a beach. She is a musician and appreciates a variety of musical genres.

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