Mastering Machine Learning with R

Master machine learning techniques with R to deliver insights for complex projects

• Get to grips with the application of Machine Learning methods using an extensive set of R packages
• Understand the benefits and potential pitfalls of using machine learning methods
• Implement the numerous powerful features offered by R with this comprehensive guide to building an independent R-based ML system

If you want to learn how to use R's machine learning capabilities to solve complex business problems, then this book is for you. Some experience with R and a working knowledge of basic statistical or machine learning will prove helpful.

• Gain deep insights to learn the applications of machine learning tools to the industry
• Manipulate data in R efficiently to prepare it for analysis
• Master the skill of recognizing techniques for effective visualization of data
• Understand why and how to create test and training data sets for analysis
• Familiarize yourself with fundamental learning methods such as linear and logistic regression
• Comprehend advanced learning methods such as support vector machines
• Realize why and how to apply unsupervised learning methods

Machine learning is a field of Artificial Intelligence to build systems that learn from data. Given the growing prominence of R―a cross-platform, zero-cost statistical programming environment―there has never been a better time to start applying machine learning to your data.

The book starts with introduction to Cross-Industry Standard Process for Data Mining. It takes you through Multivariate Regression in detail. Moving on, you will also address Classification and Regression trees. You will learn a couple of “Unsupervised techniques”. Finally, the book will walk you through text analysis and time series.

The book will deliver practical and real-world solutions to problems and variety of tasks such as complex recommendation systems. By the end of this book, you will gain expertise in performing R machine learning and will be able to build complex ML projects using R and its packages.

This is a book explains complicated concepts with easy to follow theory and real-world, practical applications. It demonstrates the power of R and machine learning extensively while highlighting the constraints.