Interpretability in Machine Learning

April 15, 2020

Ben lead the talk covering chapter 2 of the Machine Learning Intpretability book. The discussion centered on why interpretability in machine learning matters and the different tradeoffs encountered when making a model more interpretable.

The slides from the talk are available here.