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.
Details
Academic unit | Economics |
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Unit code | ECMT3185 |
Unit name | Econometrics of Machine Learning |
Session, year
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Semester 2, 2022 |
Attendance mode | Normal day |
Location | Remote |
Credit points | 6 |
Enrolment rules
Prohibitions
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QBUS3820 |
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Prerequisites
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ECMT2150 and ECMT2160 |
Corequisites
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None |
Available to study abroad and exchange students | Yes |
Teaching staff and contact details
Coordinator | Xuetao Shi, xuetao.shi@sydney.edu.au |
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