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

Ensembles dominate tabular ML, and this question tests whether you grasp that 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 Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.