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Spark Cookbook

You're reading from   Spark Cookbook With over 60 recipes on Spark, covering Spark Core, Spark SQL, Spark Streaming, MLlib, and GraphX libraries this is the perfect Spark book to always have by your side

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Product type Paperback
Published in Jul 2015
Publisher
ISBN-13 9781783987061
Length 226 pages
Edition 1st Edition
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Author (1):
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Rishi Yadav Rishi Yadav
Author Profile Icon Rishi Yadav
Rishi Yadav
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Table of Contents (14) Chapters Close

Preface 1. Getting Started with Apache Spark 2. Developing Applications with Spark FREE CHAPTER 3. External Data Sources 4. Spark SQL 5. Spark Streaming 6. Getting Started with Machine Learning Using MLlib 7. Supervised Learning with MLlib – Regression 8. Supervised Learning with MLlib – Classification 9. Unsupervised Learning with MLlib 10. Recommender Systems 11. Graph Processing Using GraphX 12. Optimizations and Performance Tuning Index

Introduction


The following is Wikipedia's definition of unsupervised learning:

"In machine learning, the problem of unsupervised learning is that of trying to find hidden structure in unlabeled data."

In contrast to supervised learning where we have labeled data to train an algorithm, in unsupervised learning we ask the algorithm to find a structure on its own. Let's take a look at the following sample dataset:

As you can see from the preceding graph, the data points are forming two clusters as follows:

In fact, clustering is the most common type of unsupervised learning algorithm.

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