This essay provides a broad overview of the sub-field of machine learning interpretability. While not exhaustive, my goal is to review conceptual frameworks, existing research, and future directions. I follow the categorizations used in Lipton et al.'s Mythos of Model Interpretability, which I think is the best paper for understanding the different definitions of interpretability. We'll go over ma
![Interpretability in Machine Learning: An Overview](https://cdn-ak-scissors.b.st-hatena.com/image/square/46b379e91d1a329e6bd9369c5a014f674a4e689c/height=288;version=1;width=512/https%3A%2F%2Fthegradient.pub%2Fcontent%2Fimages%2F2020%2F11%2Fmain-8.png)