Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Java Data Science Cookbook

You're reading from   Java Data Science Cookbook Explore the power of MLlib, DL4j, Weka, and more

Arrow left icon
Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787122536
Length 372 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Rushdi Shams Rushdi Shams
Author Profile Icon Rushdi Shams
Rushdi Shams
Arrow right icon
View More author details
Toc

Table of Contents (10) Chapters Close

Preface 1. Obtaining and Cleaning Data FREE CHAPTER 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.

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at ₹800/month. Cancel anytime