A Brief Introduction to Causal Inference in Machine Learning
<|reference_start|>A Brief Introduction to Causal Inference in Machine Learning: 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.)<|reference_end|>
@article{cho2024a,
    title={A Brief Introduction to Causal Inference in Machine Learning},
    author={Kyunghyun Cho},
    journal={arXiv preprint arXiv:2405.08793},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.08793},
    primaryClass={cs.LG}
}