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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

Summary


This chapter constitutes an extension of what was described and discussed in the previous chapters (Chapter 3, A Holistic View on Spark to Chapter 9, City Analytics on Spark). Here, we took an approach driven by data and analytical needs rather than driven by predefined projects. We also developed some predictive models to score subscribers on customer churn, on Call Center calling probabilities, and even on purchasing propensity.

In this chapter, using a real-life project of learning from telco data, we have gone through a step-by-step process of utilizing big data to serve the telco company as well as their clients, from which we processed a large amount of data on Apache Spark. We then built several models, including regression and decision tree, to predict customer churn and Call Center calls and also purchasing, with which we then developed rules for alerts and also developed scores to help the telco company and its clients. At the same time, we completed some exploratory analytics...

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