ECON 522
Applied Machine Learning in Economics credit:
Overview of different concepts, techniques, and algorithms in machine learning with a view towards applications in economics. Topics covered include regression, classification, model selection, predictive accuracy such as regularized regression, decision trees, boosting, support vector machines, and neural networks. Students acquire the skills to apply basic machine learning methods to solve economics problems. Prerequisite: ECON 500 and either ECON 502 or ECON 508 .
Topics
- regression
- classification
- model selection
- predictive accuracy such as regularized regression
- decision trees
- boosting
- support vector machines
- and neural networks
Topics explicitly listed in official catalogue description
Sources
- Course catalogue ↗2026-2027