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Root number
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458657 |
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Semester
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FS2024 |
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Type of course
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Lecture |
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Allocation to subject
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Economics |
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Type of exam
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not defined |
| Title |
Machine Learning in Economics |
| Description |
The aim of this course is to provide students with an overview of the most common machine learning methods that are currently acquiring more and more importance in the economic analysis. Both the theoretical framework and implementation technique of the methods will be presented. In particular, this course starts from the basics of model selection and introduces Lasso and Ridge regression, as well as the random tree, boosting, bagging, the random forest and its recent extension to the causal forest. All applications are in R for this course.
Assessment:
As final examination, students are expected to write a short paper (10 pages) in which they will apply one or more of the methods studied during the course. This paper accounts for 100% of the final grade. The paper will be graded with marks from 1 - 6.
Lecture:
Thursday, 14.15 - 16.00 h, PC Pool A322, UniS
1st term submission paper: 31. May, 2024
2nd term submission paper: 01 September 2024 |
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ILIAS-Link (Learning resource for course)
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No registration/deregistration in CTS (Admission in ILIAS possible).
ILIAS
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Link to another web site
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| Lecturers |
Prof. Dr.
Costanza Naguib, Teaching Staff, Faculty of Business, Economics and Social Sciences ✉
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ECTS
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4.5 |
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Recognition as optional course possible
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No |
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Grading
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1 to 6 |
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| Dates |
Thursday 14:15-16:00 Weekly
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Friday 31/5/2024 00:15-23:55
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Sunday 1/9/2024 00:15-23:55
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Rooms
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| External rooms |
A322, PC Pool, UniS
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| Students please consult the detailed view for complete information on dates, rooms and planned podcasts. |
User:
Öffentlicher Bereich
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