  This is a lecture note produced for DS-GA 3001.003 "Special Topics in DS -
Causal Inference in Machine Learning" at the Center for Data Science, New York
University in Spring, 2024. This course was created to target master's and PhD
level students with basic background in machine learning but who were not
exposed to causal inference or causal reasoning in general previously. In
particular, this course focuses on introducing such students to expand their
view and knowledge of machine learning to incorporate causal reasoning, as this
aspect is at the core of so-called out-of-distribution generalization (or lack
thereof.)
