Coursera Data Mining Class uses the Caret Package by Max Kuhn

I have been taking the Coursera Data Science track for fun over the last couple of months. Each class is about a month and it is all in R which is great. Although the classes are fairly basic I have found them enjoyable to do, and some of their examples have given me nicer ways to do things than how I have done the operations in the past. The eight class in the series is called Practical Machine Learning.  So far it has been a great ride through the Max Kuhn's Caret package. I have been using this package since 2008. I always believed that Caret had become the defacto Machine Learning package in R. Part of the reason for this is that it contains something like 187 different models within the package. The main reason for me is the unified interface to those models make it easy to try models that you are not an expert in. This makes the process of modeling better because it used to be people only used models they new well doused often which might not be the best model for the data they are working on. Caret lowers the barriers for model uses and open the door to better and more robust prediction.

If you have never used the Caret package you should try it in the Coursera Class. If you have and want to learn more here is the website. Also their is Max's book which uses Caret called Applied Predictive Modeling.