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

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