ML Fundamentals

Which activation to use where, why ReLU replaced sigmoid, why transformers moved to GELU and SwiGLU, and the failure modes (dead units, saturation, non-zero-centered outputs) interviewers ask you to diagnose.

A scannable reference for ML interviews: which loss to use for which task, why it works, when it breaks, the PyTorch gotchas that cause real bugs, and how to answer the question every interviewer asks.