Machine Learning with R

R gives you access to the cutting-edge software you need to prepare data for machine learning. No previous knowledge required – this book will take you methodically through every stage of applying machine learning.

Key Features

• Harness the power of R for statistical computing and data science
• Use R to apply common machine learning algorithms with real-world applications
• Prepare, examine, and visualize data for analysis
• Understand how to choose between machine learning models
• Packed with clear instructions to explore, forecast, and classify data

Book Description

What you will learn

• Understand the basic terminology of machine learning and how to differentiate among various machine learning approaches
• Use R to prepare data for machine learning
• Explore and visualize data with R
• Classify data using nearest neighbor methods
• Learn about Bayesian methods for classifying data
• Predict values using decision trees, rules, and support vector machines
• Forecast numeric values using linear regression
• Model data using neural networks
• Find patterns in data using association rules for market basket analysis
• Group data into clusters for segmentation
• Evaluate and improve the performance of machine learning models
• Learn specialized machine learning techniques for text mining, social network data, and ‚Äúbig‚Äù data

Who this book is for

Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.