Machine Learning for Astrophysicists

Harvard FAS

A survey course of statistical and data-driven methodologies widely utilized in astrophysics. Topics will include introductory Bayesian statistics, unsupervised methods (dimensionality reduction, density estimation, clustering), supervised methods (classification, prediction, inference), and deep learning techniques (neural networks, generative methods). This course will focus on both the theory behind these methodologies and their application to astronomical datasets. This course is open to…