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 a holistic view


As discussed in the previous section, in this section, we need to select our analytical methods or models (equations) to complete the task of mapping our business use case to machine learning methods.

To assess the impact of various factors on the sales team's success, there are many suitable models for us to use. As an exercise, we will select (a) regression models, (b) structural equation models, and (c) decision trees, mainly for their ease of interpretation as well as their implementablility on Spark.

Once we finalize our decision for analytical methods or models, we will need to prepare the dependent variable and also prepare for coding; we will discuss these one by one in the following section.

Regression modeling

To get ready for regression modeling on Spark, there are three issues for us to take care of:

  • Linear regression or logistic regression.

    Regression is the most mature and also the most widely used model to represent the impact of various factors on one...