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Apache Spark Machine Learning Blueprints

You're reading from   Apache Spark Machine Learning Blueprints Develop a range of cutting-edge machine learning projects with Apache Spark using this actionable guide

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Product type Paperback
Published in May 2016
Publisher Packt
ISBN-13 9781785880391
Length 252 pages
Edition 1st Edition
Languages
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Author (1):
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Alex Liu Alex Liu
Author Profile Icon Alex Liu
Alex Liu
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Table of Contents (13) Chapters Close

Preface 1. Spark for Machine Learning FREE CHAPTER 2. Data Preparation for Spark ML 3. A Holistic View on Spark 4. Fraud Detection on Spark 5. Risk Scoring on Spark 6. Churn Prediction on Spark 7. Recommendations on Spark 8. Learning Analytics on Spark 9. City Analytics on Spark 10. Learning Telco Data on Spark 11. Modeling Open Data on Spark Index

Apache Spark for a recommendation engine


In this section, we will continue to demonstrate Spark's computation speed and ease of coding for a real-life project of movie recommendation, but to be completed by SPSS on Apache Spark.

SPSS is a widely used software package for statistical analysis. SPSS originally stood for Statistical Package for Social Science, but it is also used by market researchers, health researchers, survey companies, government, education researchers, marketing organizations, data miners, and others. Long produced by SPSS Inc., it was acquired by IBM in 2009. Since then, IBM further developed it and turned it into a popular tool for data scientists and machine learning professionals. To make Spark available to SPSS users, IBM developed technologies making SPSS Spark integration easy, which will be covered in this chapter.

The use case

This project is to help movie rental company ZHO improve its movie recommendations to its customers.

The main data set contains tens of million...

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