Feb 4, 2026 — 18 min — Platform & AI
Machine Learning Terms That Make Model Reviews Better
A practical ML terminology guide for model reviews where feature definitions, data splits, task type, optimization behavior, overfitting risk, regularization, ensembles, and embeddings need to be discussed precisely.
Outcome: Gave peers a review-ready vocabulary for inspecting ML systems by connecting core terms to design choices, failure modes, and release questions.