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

Fundamental aspects of recommendation engines

While the basic intent of showing recommendations is to push sales, they actually serve just beyond the better sales concept. Highly personalized content is something recommendation engines are able to deliver. This essentially means that recommendation engines on a retail platform such as Amazon are able to offer the right content to the right customer at the right time through the right channel. It makes sense to provide personalized content; after all, there is no point in showing an irrelevant product to a customer. Also, with the lower attention spans of customers, businesses want to be able to maximize their selling opportunities by showing the right products and encouraging them to buy the right products. At a very high level, personalized content recommendation is achieved in AI in several ways:

  • Mapping similar products that...