Compare bagging and boosting, and random forests vs gradient boosting. When do you use each?

Ensembles dominate tabular ML, and this question checks whether you know they attack different parts of the error. The signal is bagging-reduces-variance vs boosting-reduces-bias and why GBMs win on tabular data. Here is the answer.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.