| Dozent/in |
Prof. Dr. Helmut Farbmacher |
| Veranstaltungsart |
Doktorierendenkolloquium |
| Code |
HS221319 |
| Semester |
Herbstsemester 2022 |
| Durchführender Fachbereich |
Gesundheitswissenschaften |
| Studienstufe |
Doktorat |
| Termin/e |
Mo, 19.09.2022, 08:15 - 18:00 Uhr, HS 4
Di, 20.09.2022, 08:15 - 18:00 Uhr, HS 12
Mi, 21.09.2022, 08:15 - 18:00 Uhr, HS 4
Do, 22.09.2022, 08:15 - 18:00 Uhr, HS 14
Fr, 23.09.2022, 08:15 - 18:00 Uhr, 4.B47 |
| Inhalt |
The course covers a selection of state-of-the-art methods in econometrics and machine learning. It aims to provide students with a sound understanding of the methods discussed, such that they are able to do research using modern econometric techniques, as well as critically assess existing studies. |
| Lernziele |
In particular, the course will likely cover the following topics:
• Regression Shrinkage Methods (Ridge, Lasso, Elastic Net)
• Decision Trees, Random/Causal Forests
• Advanced Identification Strategies (e.g., Double Machine Learning)
• Introduction to Neural Networks |
| Voraussetzungen |
A solid introductory course in econometrics. Preferably some basic knowledge of R and Python. Participants should bring their own laptop with R and/or Python installed. The target audience are PhD students. |
| Sprache |
Englisch |
| Anmeldung |
https://www.sggoe.ch/events/machine-learning-in-health-economics.html |
| Prüfung |
Successful participation (no explicit grading) |
| Hinweise |
The course covers a selection of state-of-the-art methods in econometrics and machine learning. It aims to provide students with a sound understanding of the methods discussed, such that they are able to do research using modern econometric techniques, as well as critically assess existing studies. |
| Hörer-/innen |
Nein |
| Kontakt |
Prof. Dr. Stefan Boes, stefan.boes@unilu.ch |
| Material |
Recommended textbooks:
• Goodfellow Ian, Bengio Yoshua and Courville Aaron. Deep Learning, MIT Press, available here
• Bishop Christopher. Pattern Recognition and Machine Learning, Springer, available here
• Hansen Bruce. Econometrics, available here
• Hastie Trevor, Tibshirani Robert and Friedman Jerome. The Elements of Statistical Learning, Springer, available here
• James Gareth, Witten Daniela, Hastie Trevor and Tibshirani Robert. An Introduction to Statistical
Learning with Applications in R, Springer, available here |