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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 explored the four foundational pillars of OOP: abstraction, encapsulation, inheritance, and polymorphism. We illustrated their application through the development of a LootCrate class in a game project. Abstraction was highlighted as the essential process of simplifying complex systems, enabling us to focus on the relevant aspects of a class while hiding unnecessary details. By abstracting a new LootCrate class, we identified its main features and behaviors, such as the ability to drop items with a specified drop rate. This helps in making the game more engaging for players. This abstraction clarified not only the class’s purpose but also how it should interact with other parts of the game, providing a clear roadmap for its implementation.

Following abstraction, we talked about encapsulation, which protects the internal state of objects and ensures that only necessary interfaces are exposed to other parts of the application. This principle was...

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R Machine Learning Projects
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