Seminar on Machine Learning
Completed
This seminar consists of an introductory exploration of both theory and applications of machine learnig models.
The plan of the talks goes as follows:
| Date | Topic | Speaker | ||||
|---|---|---|---|---|---|---|
| 19.02.2024 | Introduction | S. Koovely | ||||
| 05.03.2024 | Hypothesis Classes & PAC Learnability I | D. Sanchez | ||||
| 12.03.2024 | PAC Learnability II & No-free Lunch Thm. | A. Schlegel | ||||
| 19.03.2024 | VC Dimension & Model Selection | F. C. Steiner | ||||
| 26.03.2024 | Linear Regression | S. S. Tajana | ||||
| 02.04.2024 | Decision Trees & Random Forests | L. Schäppi & M. Ineichen | ||||
| 09.04.2024 | SVM & Kernel Method | W. Liu | ||||
| 16.04.2024 | Dimensionality Reduction | A. Mokhova & R. A. Hugener | ||||
| 30.04.2024 | Clustering | M. Ambühl | ||||
| 07.05.2024 | Feed-Forward Neural Networks | V. Gojani | ||||
| 21.05.2024 | Tutorial with MNIST Dataset | S. Koovely |
\