Prerequisites: ECON 216A; or equivalent; graduate standing
Description: Introduces machine learning tools for big data analysis in economics. Focuses on critical toolkits (methods and softwares) and applications to big data in economics. Topics include regression and classification, regularization, resampling methods, decision trees, boosting, and deep learning.
Credit: Credit is awarded for one of the following ECON 220 or STAT 208.