Predict which orders will be sent back, compare a forest with one tree and build a call list.
New to this? See the worked example firstA random forest is many decision trees voting together. In these questions you predict which online orders will be returned, compare the forest with a single tree, read feature importance and tune the forest with a grid search.
It is one of the most used models on table data at work, so expect questions on out-of-bag score, number of trees and feature importance.
If you are new to it, read the worked example first, then solve the questions in order: the early ones explore the data and train a first model, the middle ones test it on rows it has not seen, and the last ones tune it and turn the result into a business decision.