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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

The work presented in this chapter is a further extension of Chapter 10, Learning Telco Data on Spark, as well as Chapter 9, City Analytics on Spark. It is a very special extension of Chapter 9, City Analytics on Spark, as both chapters are using open datasets. It is also an extension of Chapter 10, Learning Telco Data on Spark, as both chapters take a dynamic approach so that readers can take advantage of all the learned techniques to achieve better machine learning results and also to develop the best analytical solutions. Therefore, this chapter may be used as a review chapter, as well as a special chapter for you to synthesize all the knowledge learned.

In this chapter, with a real-life project of learning from open data, we have repeated the same step-by-step RM4Es process as used in the previous chapters, from which we processed open data on Apache Spark and then selected models (equations). For each model, we estimated their coefficients and then evaluated these models against...

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