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

Implementing a Jokes Recommendation Engine

I am sure this is something you have experienced as well: while shopping for a cellphone on Amazon, you are also shown some product recommendations of mobile accessories, such as screen guards and phone cases. Not very surprisingly, most of us end up buying one or more of these recommendations! The primary purpose of a recommendation engine in an e-commerce site is to lure buyers into purchasing more from vendors. Of course, this is no different from a salesperson trying to up-sell or cross-sell to customers in a physical store.

You may recollect the Customers Who Bought This Item Also Bought This heading on Amazon (or any e-commerce site) where recommendations are shown. The aim of these recommendations is to get you to buy not just one product but a product combo, therefore pushing the sales revenues in an upward direction. Recommendations...