The unit introduces the theory and application of statistical machine learning. Topics covered include supervised versus unsupervised learning; regression and classification; resampling methods including cross-validation and Bootstrap; regularisation and shrinkage approaches such as Lasso; tree-based methods including decision tree and random forest; and support vector machines. The unit focuses on the applications of statistical machine learning in economics, and computer software such as R and Matlab are used throughout the unit.
|Unit name||Econometrics of Machine Learning|
|Semester 2, 2022|
|Attendance mode||Normal day|
|ECMT2150 and ECMT2160|
|Available to study abroad and exchange students||
Teaching staff and contact details
|Coordinator||Xuetao Shi, firstname.lastname@example.org|