Course: STAT 37795
Title: Causal Inference with Machine Learning
Instructor(s): Victor Veitch
Teaching Assistant(s):
Class Schedule: Sec 1: TR 3:30 PM-4:50 PM in Jones 226
Description: This is a seminar on the use of causality in building robust and trustworthy machine learning systems. Standard machine learning pipelines have a wide range of issues in practice, including reliance on apparently irrelevant features, poor performance when deployed in domains that are mismatched to their training environment, and discriminatory or unfair behavior. This course will cover the use of causality in defining, understanding, and mitigating these failure modes.