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  • Book Overview & Buying Learning Apache Mahout
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Learning Apache Mahout

Learning Apache Mahout

By : Chandramani Tiwary
3 (1)
Buy this Book
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Learning Apache Mahout

Learning Apache Mahout

3 (1)
By: Chandramani Tiwary
Buy this Book

Overview of this book

If you are a Java developer and want to use Mahout and machine learning to solve Big Data Analytics use cases then this book is for you. Familiarity with shell scripts is assumed but no prior experience is required.
Table of Contents (12 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Introduction to Mahout
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1. Introduction to Mahout
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Why Mahout
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When Mahout
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How Mahout
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Summary
2
2. Core Concepts in Machine Learning
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2. Core Concepts in Machine Learning
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Supervised learning
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Unsupervised learning
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Recommender system
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Model efficacy
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Summary
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3. Feature Engineering
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3. Feature Engineering
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Feature engineering
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Summary
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4. Classification with Mahout
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4. Classification with Mahout
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Classification
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Logistic regression
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Adaptive regression model
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Code example with logistic regression
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Random forest
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Naïve Bayes classifier
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Summary
5
5. Frequent Pattern Mining and Topic Modeling
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5. Frequent Pattern Mining and Topic Modeling
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Frequent pattern mining
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Importing the Mahout source code into Eclipse
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Frequent pattern mining with Mahout
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Summary
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6. Recommendation with Mahout
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6. Recommendation with Mahout
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Collaborative filtering
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Summary
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7. Clustering with Mahout
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7. Clustering with Mahout
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k-means
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Canopy clustering
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Fuzzy k-means
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A Mahout command-line example
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A Mahout Java example
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Summary
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8. New Paradigm in Mahout
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8. New Paradigm in Mahout
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Moving beyond MapReduce
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Apache Spark
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In-core types
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Spark Mahout basics
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Linear regression with Mahout Spark
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Summary
9
9. Case Study – Churn Analytics and Customer Segmentation
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9. Case Study – Churn Analytics and Customer Segmentation
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Churn analytics
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Summary
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10. Case Study – Text Analytics
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10. Case Study – Text Analytics
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Text analytics
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Clustering text
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Categorizing text
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Summary
11
Index
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Index

Importing the Mahout source code into Eclipse

It's a good idea to look at the source code of Mahout, as it will give you additional insights into the working of machine learning algorithms and Mahout commands. In this section, we will be exploring and modifying some of the source files of Mahout. For that, we need to import the source code into Eclipse. Mahout source code is packaged in Maven and if all the configuration steps of Chapter 1, Introduction to Mahout, were followed, we should be ready to import the source code into Eclipse.

Let's start with downloading the code folder. Please go to the URL http://archive.apache.org/dist/mahout/0.9 and download the file mahout-distribution-0.9-src.tar.gz. Ideally the file should be copied to the Eclipse workspace directory, but any location can be used. The next step is to extract the archive in the folder where the archive mahout-distribution-0.9-src.tar.gz has been copied to. For this, we will execute the following command:

tar -xf...
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Tech Concepts
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Programming languages
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Learning Apache Mahout
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