[This article was first published on Revolutions, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
If you're looking to get started with data science in R, a great place to start is OnePageR by Graham Williams. (Graham is the creator of Rattle, author of Data Mining with Rattle and R, and Director of Data Science at Microsoft.) This free (CC-licensed) resource is a series of hands-on mini-chapters and associated R code, organized into four main topic areas:
- Data Science: introductions to data science, data mining, literate programming, and the R language
- Dealing with Data: Reading data files and open access data, basic explorations and visualizations, and two case studies
- Building Models: with tutorials for many kinds of models, including association analysis, ensemble models, and multivariate adaptive regression splines
- Advanced R and Analytics: with topics including writing functions, parallel processing, and text mining.
Example data files are provided for use in all chapters. There are also two very useful appendix chapters; an R Style Guide, and a guide to creating an R package.
OnePageR is a continual work in progress, and is regularly updated to incorporate advances in R and the R package ecosystem. To download the materials, follow the link below.
Togaware: OnePageR
To leave a comment for the author, please follow the link and comment on their blog: Revolutions.
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.