Book Image

Apache Spark Machine Learning Blueprints

By : Alex Liu
Book Image

Apache Spark Machine Learning Blueprints

By: Alex Liu

Overview of this book

There's a reason why Apache Spark has become one of the most popular tools in Machine Learning – its ability to handle huge datasets at an impressive speed means you can be much more responsive to the data at your disposal. This book shows you Spark at its very best, demonstrating how to connect it with R and unlock maximum value not only from the tool but also from your data. Packed with a range of project "blueprints" that demonstrate some of the most interesting challenges that Spark can help you tackle, you'll find out how to use Spark notebooks and access, clean, and join different datasets before putting your knowledge into practice with some real-world projects, in which you will see how Spark Machine Learning can help you with everything from fraud detection to analyzing customer attrition. You'll also find out how to build a recommendation engine using Spark's parallel computing powers.
Table of Contents (18 chapters)
Apache Spark Machine Learning Blueprints
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
Index

Chapter 6. Churn Prediction on Spark

In this chapter, we will focus on the utilization of some Apache Spark machine learning libraries, especially MLlib, as applied to a churn predictive modeling project.

Specifically, in this chapter, we will first review machine learning methods and the related computing for a churn prediction project, and will then discuss how Apache Spark MLlib makes things easy and fast. At the same time, with a real life churn prediction example, we will illustrate the step-by-step process of predicting churns with big data. The following topics will be covered in this chapter:

  • Spark for churn prediction

  • Methods for churn prediction

  • Feature preparation

  • Model estimation

  • Model evaluation

  • Results explanation

  • Model deployment