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Root number
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458657 |
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Semester
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FS2025 |
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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 |
*** IMPORTANT ***
For the most updated administrative course information (date changes, room changes etc) please always refer to the KSL page only and not to the Info page in ILIAS – the ILIAS infopage will not be updated!
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:01.06.2025
2nd term submission paper: 01.09.2025 |
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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, Department of Economics ✉
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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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Sunday 1/6/2025 00:05-23:55
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Monday 1/9/2025 00:05-23:55
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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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