Book Image

Mastering Machine Learning with R, Second Edition - Second Edition

Book Image

Mastering Machine Learning with R, Second Edition - Second Edition

Overview of this book

This book will teach you advanced techniques in machine learning with the latest code in R 3.3.2. You will delve into statistical learning theory and supervised learning; design efficient algorithms; learn about creating Recommendation Engines; use multi-class classification and deep learning; and more. You will explore, in depth, topics such as data mining, classification, clustering, regression, predictive modeling, anomaly detection, boosted trees with XGBOOST, and more. More than just knowing the outcome, you’ll understand how these concepts work and what they do. With a slow learning curve on topics such as neural networks, you will explore deep learning, and more. By the end of this book, you will be able to perform machine learning with R in the cloud using AWS in various scenarios with different datasets.
Table of Contents (23 chapters)
Title Page
Credits
About the Author
About the Reviewers
Packt Upsell
Customer Feedback
Preface
16
Sources

Chapter 15. R Fundamentals

"One of my most productive days was throwing away 1,000 lines of code."                                                                                                            - Ken Thompson

This chapter covers the basic programming syntax functions and capabilities of R. Its intention is to introduce you to R and accelerate your learning. The objectives are as follows:

  • Installing R and RStudio
  • Creating and exploring vectors
  • Creating data frames and matrices
  • Exploring mathematical and statistical functions
  • Building simple plots
  • Introducing dplyr data manipulation
  • Installing and loading packages

All of the examples in this Appendix are covered in one way or another in the preceding chapters. However, if you are completely new to R, this is a great starting point. It may accelerate your understanding of the content in the chapters.