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


In this chapter, we learned various NLP techniques, namely BoW, Word2vec, GloVe, and fastText. We built projects involving these techniques to perform sentiment analysis on an Amazon reviews dataset. The projects that were built involved two approaches, making use of pretrained word embeddings and building the word embeddings from our own dataset. We tried both these approaches to represent text in a format that can be consumed by ML algorithms that resulted in models with the ability to perform sentiment analysis.

In the next chapter, we will learn about customer segmentation by making use of a wholesale dataset. We will look at customer segmentation as an unsupervised problem and build projects with various techniques that can identify inherent groups within the e-commerce company's customer base. Come, let's explore the world of building an e-commerce customer...