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R Machine Learning Projects

R Machine Learning Projects

By : Dr. Sunil Kumar Chinnamgari
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R Machine Learning Projects

R Machine Learning Projects

1 (1)
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)
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10
The Road Ahead

Understanding RL

RL is a very important area but is sometimes overlooked by practitioners for solving complex, real-world problems. It is unfortunate that even most ML textbooks focus only on supervised and unsupervised learning while totally ignorning RL.

RL as an area has picked up momentum in recent years; however, its origins date back to 1980. It was invented by Rich Sutton and Andrew Barto, Rich's PhD thesis advisor. It was thought of as archaic, even back in the 1980s. Rich, however, believed in RL and its promise, maintaining that it would eventually be recognized.

A quick Google search with the term RL shows that RL methods are often used in games, such as checkers and chess. Gaming problems are problems that require taking actions over time to find a long-term optimal solution to a dynamic problem. They are dynamic in the sense that the conditions are constantly...

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