Astrophysical Data Analytics

3 credit hours · Graduate

Students discuss statistical and computational techniques common to all astronomy research subfields with an emphasis on state-of-the-art techniques in data mining and machine learning. Topics include a review of probability and statistical distributions, classical and Bayesian statistical inference, density estimation, clustering, principal component analysis, regression, and classification.