Inspired by this article i thought about gather here all multimedia resources that i know to learn use R. Today The post MOOCs and courses to learn R appeared first on Flavio Barros .

Inspired by this article i thought about gather here all multimedia resources that i know to learn use R. Today The post MOOCs and courses to learn R appeared first on Flavio Barros .

In case you missed them, here are some articles from February of particular interest to R users: A statistical analysis of various forecasting methods (using R) leads to correct predictions for 21 of 24 Oscars awards. There are now 123 R User Groups worldwide, and applications for Revolution Analytics sponsorship grants are open until March 31. Revolution Analytics was...

It is our pleasure to once again offer the intensive R beginner level course for the third time! Beginning this Sunday, the 35 hour course will walk you through the basic operations and characteristics of R, all the way to having a firm understanding of data manipulation and visualization. Also launching this weekend are two... Read more »

Graham Williams is the Lead Data Scientist at the Australian Taxation Office, and the creator of Rattle, an open-source GUI for data mining with R. (Check out some recent reviews/demos of Rattle on this blog here and here.) Dr Williams continues his many contributions to the R community with One Page R, a "Survival Guide to Data Science with...

Now that the conference and the Bayesian non-parametric satellite workshop (thanks to Judith!) are over, with (almost) everyone back home, and that the post-partum conference blues settles in (!), I can reflect on how things ran for those meetings and what I could have done to improve them… (Not yet considering to propose a second

Guest post by Vivian Zhang, original post. You can sign up for our Sunday Intensive beginner level R classes at NYC Data Science Academy meetup page or email vivian.zhang@supstat.com for more info. Brief: The course (which will meet five Sundays) will start from the basics, introducing the building blocks used for programming in R and building intuition for writing clean and robust code....

by Joseph Rickert The world may indeed be awash with data, however, it is not always easy to find a suitable data set when you need one. As the number of people becoming involved with R and data science increases so does the need for interesting data sets for creating examples, showcasing machine learning algorithms and developing statistical analyses....

In R’s partitioning approach, observations are divided into K groups and reshuffled to form the most cohesive clusters possible according to a given criterion. There are two methods—K-means and partitioning around mediods (PAM). In this article, based on chapter 16 of R in Action, Second Edition, author Rob Kabacoff discusses K-means clustering. Read more »

R provides us with excellent resources to mine data, and there are some good overviews out there: Yanchang’s website with Examples and a nice reference card The rattle-package that introduces a nice GUI for R, and Graham William’s compendium of tools The caret-package that offers a unified interface to running a multitude of model builders.

by Joseph Rickert The basic way to plot a classification or regression tree built with R’s rpart() function is just to call plot. However, in general, the results just aren’t pretty. As it turns out, for some time now there has been a better way to plot rpart() trees: the prp() function in Stephen Milborrow’s rpart.plot package. This function...

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