As we believe you may know, we are having a webinar tomorrow (June 19th, 2013) on Predictive Analytics. During this webinar, you are going to be introduced to R, learn how to build a predictive model and also how to carry insightful analysis through visualization.
As learning a new language can be a really difficult and painful process, we thought that it would be a valuable idea to share useful links for R resources with you. If you can spare some time to read some of these links, we believe that this first briefing will enable you to come with a better background to our webinar.
So, what do you say? Are you in for a reading and for reducing your learning curve?
/> Choose your nearest download location and click on the appropriate link
/> RStudio : href="http://www.rstudio.com/" >http://www.rstudio.com/
/> Guide to getting started with RGoogleAnalytics : href="http://bit.ly/11kUgzI">http://bit.ly/11kUgzI
/> Guide to getting started with ggplot2 : href="http://www.cookbook-r.com/Graphs/">http://www.cookbook-r.com/Graphs/
/> Ggplot2 chart chooser : href="http://www.yaksis.com/posts/r-chart-chooser.html" >http://www.yaksis.com/posts/r-chart-chooser.html
/> Finding additional R packages for your domain : href="http://cran.r-project.org/web/views/" >http://cran.r-project.org/web/views/
/> Additional Ideas for Predictive modelling :http://bit.ly/13XyCCK
Courses on R
A Prezi tour of the R ecosystem :
/> R news and tutorials from prominent R blogs : href="http://www.r-bloggers.com/" >http://www.r-bloggers.com/
/> A search engine for R: href="http://www.rseek.org/">http://www.rseek.org/
If you come across more resources, please ensure that you drop a comment below.