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Mastering Machine Learning with R

You're reading from   Mastering Machine Learning with R Master machine learning techniques with R to deliver insights for complex projects

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Product type Paperback
Published in Oct 2015
Publisher
ISBN-13 9781783984527
Length 400 pages
Edition 1st Edition
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Author (1):
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Cory Lesmeister Cory Lesmeister
Author Profile Icon Cory Lesmeister
Cory Lesmeister
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Table of Contents (15) Chapters Close

Preface 1. A Process for Success FREE CHAPTER 2. Linear Regression – The Blocking and Tackling of Machine Learning 3. Logistic Regression and Discriminant Analysis 4. Advanced Feature Selection in Linear Models 5. More Classification Techniques – K-Nearest Neighbors and Support Vector Machines 6. Classification and Regression Trees 7. Neural Networks 8. Cluster Analysis 9. Principal Components Analysis 10. Market Basket Analysis and Recommendation Engines 11. Time Series and Causality 12. Text Mining A. R Fundamentals Index

Introduction

This chapter covers the basic programming syntax functions and capabilities of R. It has been put forward to introduce you to R and accelerate your learning. The objectives are as follows:

  • Install R and RStudio
  • Create and explore vectors
  • Create data frames and matrices
  • Explore mathematical and statistical functions
  • Build simple plots
  • Install and load 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.

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