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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 (19 chapters)
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Part 1: Object-Oriented Design Principles
6
Part 2: Basic Design Patterns
12
Part 3: Advanced Design Patterns

Summary

In this chapter, we learned about the Decorator pattern and its application in creating dynamic power-up systems for games. The Decorator pattern is a structural design pattern that allows us to wrap objects with additional functionalities at runtime without altering their underlying code, as we learned in this chapter. This approach adheres to the open-closed principle, which promotes extending functionality while keeping the original class intact. By applying this pattern, we learned that we can flexibly add or remove features to an object during the game, such as modifying player attributes, including movement speed, jump height, and attack strength when power-ups are collected.

We explored how the Decorator pattern works by wrapping a base object, in this case, the Stats class, with new behaviors through decorator objects. The decorators act as wrappers, allowing us to stack multiple power-ups and apply their effects in different combinations. For instance, when a player...

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R Machine Learning Projects
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