gradient descent

An ML coding screen that doubles as a calculus check. Interviewers watch whether you can write the MSE gradient without looking it up, explain what the learning rate actually does, and say out loud when you'd just solve the normal equation instead.

A two-minute explanation, then the real test: learning-rate pathologies, why we use mini-batches, and the one practical diagnosis, reading a loss curve, that customer-facing engineers actually need.

Gradient descent is walking downhill on the loss surface, one step proportional to the slope. Knowing when to stop is the part that separates people who have trained models from people who have read about them: it is the validation curve, not the training curve, that tells you.