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Mastering Machine Learning with R, Second Edition

You're reading from   Mastering Machine Learning with R, Second Edition Advanced prediction, algorithms, and learning methods with R 3.x

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781787287471
Length 420 pages
Edition 2nd Edition
Languages
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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 (17) Chapters Close

Preface 1. A Process for Success 2. Linear Regression - The Blocking and Tackling of Machine Learning FREE CHAPTER 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 and Deep Learning 8. Cluster Analysis 9. Principal Components Analysis 10. Market Basket Analysis, Recommendation Engines, and Sequential Analysis 11. Creating Ensembles and Multiclass Classification 12. Time Series and Causality 13. Text Mining 14. R on the Cloud 15. R Fundamentals 16. Sources

Getting R up-and-running

We want to accomplish two things here: first, install the latest version of R and second, install RStudio, which is an Integrated Development Environment (IDE) for R.

Let's start by going to R's homepage at https://www.r-project.org/. This page will look similar to the following screenshot:

You can see that there is a link, download R, and in the News section the latest R version is 3.3.2 (Sincere Pumpkin Patch), which was released on 2016-10-31. Version 3.3.3 is scheduled for release in March. Now, click one of the links, either CRAN under Download or download R under Getting Started, and you will come to the following screen, which has CRAN Mirrors:

These are the links, by country and sorted alphabetically, that will take you to the download page. Being in the USA, I will scroll down and find many links available:

Once you find a similar link that is close to your location...

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