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

Methods for recommendation


In the previous section, we described the use case of building a movie recommendation engine for the company ZHO and also prepared SPSS on the Spark computing platform. In this section, as before, we need to select our analytical methods (equations) for this movie recommendation project, which again means mapping our use case to machine learning methods.

For this exercise, we will use collaborative filtering because this analytical method is well developed and tested on many recommendation projects. At the same time, analytical processes and related algorithms are also well-developed for this method, which are available in R as well as MLlib.

By following the same methodology, once we finalize our decision for analytical methods or models, we will then need to prepare the coding.

Collaborative filtering

Collaborative filtering is a method used very commonly to build recommender systems. Simply speaking, collaborative filtering is an analytical method of producing predictions...