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Java Data Science Cookbook

You're reading from  Java Data Science Cookbook

Product type Book
Published in Mar 2017
Publisher Packt
ISBN-13 9781787122536
Pages 372 pages
Edition 1st Edition
Languages
Author (1):
Rushdi Shams Rushdi Shams
Profile icon Rushdi Shams
Toc

Table of Contents (16) Chapters close

Java Data Science Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Obtaining and Cleaning Data 2. Indexing and Searching Data 3. Analyzing Data Statistically 4. Learning from Data - Part 1 5. Learning from Data - Part 2 6. Retrieving Information from Text Data 7. Handling Big Data 8. Learn Deeply from Data 9. Visualizing Data

Introduction


In Chapter 4, Learn from Data - Part 1, we used the Weka machine learning workbench for different recipes for classification, clustering, association rule mining, feature selection, and so on. We also mentioned in that chapter that Weka is not the only tool that is written in Java to learn patterns from data. There are other tools that can perform similar tasks. Examples of such tools include but are not limited to Java Machine Learning (Java-ML) library, Massive Online Analysis (MOA), and Stanford machine learning libraries.

In this chapter, we will be focusing on bits and pieces of these other tools to conduct machine learning analysis on data.

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