Compare activation functions (sigmoid, tanh, ReLU, GELU, softmax) and when to use each.
A staple that tests whether you know why ReLU displaced sigmoid and how to pair the output activation with the loss. What matters is telling the vanishing-gradient story correctly. 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.
A staple that tests whether you know why ReLU displaced sigmoid and how to pair the output activation with the loss. What matters is telling the vanishing-gradient story correctly. Here is the answer.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
