The publication of An Introduction to Statistical Learning with Applications in R (download the book pdf) provides a gentle introduction with lots of R code. The book achieves a nice balance and well worth looking at both for the beginner and the more experienced needing to explain to others with less training. As a bonus, Stanford's OpenEdX has scheduled a MOOC by Hastie and Tibshirani beginning in January 21 using this textbook.
Monday, January 6, 2014
An Introduction to Statistical Learning with Applications in R
how to run the R package softImpute that makes all this happen. But it can be overwhelming trying to learn about the underlying mechanism in enough detail that you have some confidence that you know what you are doing. One does not want to spend the time necessary to become a statistician, yet we need be aware of when and how to use specific models, and what can go wrong, and what to do when something goes wrong. At least with R, one can run analyses on data sets and work through concrete examples.