I need to recommend an R book (or an online tutorial) for someone who is well experienced in programming languages like Python and Java and knows a reasonable amount of statistics. What is the best resource for her to get productive in R quickly?

asked Jul 08 '13 at 16:55

Delip%20Rao's gravatar image

Delip Rao
6653912


5 Answers:

I found R Cookbook very useful http://shop.oreilly.com/product/9780596809164.do A lot of examples, easy to get the R language structure esp. when you already know other languages.

answered Jul 08 '13 at 18:00

Vladimir%20Chupakhin's gravatar image

Vladimir Chupakhin
462

edited Jul 08 '13 at 18:13

The best book to be productive in R quickly is "Applied Predictive Modeling" by Max Kuhn and Kjell Johnson. The best book on programming in R is "The Art of R Programming" by Norman Matloff.

answered Jul 08 '13 at 17:17

Stephen%20Oates's gravatar image

Stephen Oates
1

I second "The Art of R Programming"

(Jul 09 '13 at 22:13) Dan Ryan

Here is a post that has a list of books. There is an R book mentioned above the code which is good. Yet another excellent resource are forums like stackoverflow, but the process of learning can be slow. There is of course the cran project site itself here but again its not in an easy readable format the book offers. Hope that helps

answered Jul 08 '13 at 20:38

Broccoli's gravatar image

Broccoli
15112

Here is a post that has a list of books. There is an R book mentioned above the code which is good. Yet another excellent resource are forums like stackoverflow, but the process of learning can be slow. There is of course the cran project site itself here but again its not in an easy readable format the book offers. Hope that helps

answered Jul 08 '13 at 20:38

Broccoli's gravatar image

Broccoli
15112

There is a book called "Machine Learning for Hackers"

Here it's abstract:

If you’re an experienced programmer interested in crunching data, this book will get you started with machine learning—a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.

Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you’ll learn how to analyze sample datasets and write simple machine learning algorithms. Machine Learning for Hackers is ideal for programmers from any background, including business, government, and academic research.

Develop a naïve Bayesian classifier to determine if an email is spam, based only on its text
Use linear regression to predict the number of page views for the top 1,000 websites
Learn optimization techniques by attempting to break a simple letter cipher
Compare and contrast U.S. Senators statistically, based on their voting records
*Build a “whom to follow” recommendation system from Twitter data

answered Jul 10 '13 at 08:33

edersantana's gravatar image

edersantana
155259

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