Book Image

Advanced Machine Learning with R

By : Cory Lesmeister, Dr. Sunil Kumar Chinnamgari
Book Image

Advanced Machine Learning with R

By: Cory Lesmeister, Dr. Sunil Kumar Chinnamgari

Overview of this book

R is one of the most popular languages when it comes to exploring the mathematical side of machine learning and easily performing computational statistics. This Learning Path shows you how to leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. You’ll work through realistic projects such as building powerful machine learning models with ensembles to predict employee attrition. Next, you’ll explore different clustering techniques to segment customers using wholesale data and even apply TensorFlow and Keras-R for performing advanced computations. Each chapter will help you implement advanced machine learning algorithms using real-world examples. You’ll also be introduced to reinforcement learning along with its use cases and models. Finally, this Learning Path will provide you with a glimpse into how some of these black box models can be diagnosed and understood. By the end of this Learning Path, you’ll be equipped with the skills you need to deploy machine learning techniques in your own projects.
Table of Contents (30 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Chapter 18. Customer Segmentation Using Wholesale Data

In today's competitive world, the success of an organization largely depends on how much it understands its customers' behavior. Understanding each customer individually to better tailor the organizational effort to individual needs is a very expensive task. Based on the size of the organization, this task can be very challenging as well. As an alternative, organizations rely on something called segmentation, which attempts to categorize customers into groups based on identified similarities. This critical aspect of customer segmentation allows organizations to extend their efforts to the individual needs of various customer subsets (if not catering to individual needs), therefore reaping greater benefits.

In this chapter, we will learn about the concept and importance of customer segmentation. We'll then deep dive into learning the various machine learning (ML) methods to identify subgroups of customers based on customer characteristics...