Random forest is a highly versatile machine learning method with numerous applications ranging from marketing to healthcare and insurance. It can be used to model the impact of marketing on customer acquisition, retention, and churn or to predict disease risk and susceptibility in patients.
Random forest is a capable of regression and classification. It can handle a large number of features, and it's helpful for estimating which or your variables are important in the underlying data being modeled.
This is a post about random forests using Python.