https://thegradient.pub/interpretability-in-ml-a-broad-overview/
Interpretability in Machine Learning: An Overview
21.Nov.2020
Owen Shen
“Broadly, interpretability focuses on the how. It’s focused on getting some notion of an explanation for the decisions made by our models…. First, interpretability in machine learning is useful because it can aid in trust. As humans, we may be reluctant to rely on machine learning models…”