Book Image

R Machine Learning Projects

By : Dr. Sunil Kumar Chinnamgari
Book Image

R Machine Learning Projects

By: Dr. Sunil Kumar Chinnamgari

Overview of this book

R is one of the most popular languages when it comes to performing computational statistics (statistical computing) easily and exploring the mathematical side of machine learning. With this book, you will leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. This book will help you test your knowledge and skills, guiding you on how to build easily through to complex machine learning projects. You will first learn how to build powerful machine learning models with ensembles to predict employee attrition. Next, you’ll implement a joke recommendation engine and learn how to perform sentiment analysis on Amazon reviews. You’ll also explore different clustering techniques to segment customers using wholesale data. In addition to this, the book will get you acquainted with credit card fraud detection using autoencoders, and reinforcement learning to make predictions and win on a casino slot machine. By the end of the book, you will be equipped to confidently perform complex tasks to build research and commercial projects for automated operations.
Table of Contents (12 chapters)
The Road Ahead

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...