Linear Model Selection and Regularization (Part 2)
Jacek Gulgowski
| Mon Jan 19, 11:30-13:30 (10 days from now) | |
| Lecture held in Room 1 at the IMPAS, Room 1.14 at the Institute of Informatics (University of Gdańsk). |
Abstract: In the second session, we turn to Regularization Methods, focusing on ridge regression and the lasso. We'll examine how these techniques use penalty terms to control model flexibility, reduce overfitting, and enhance prediction accuracy, with hands-on Python examples illustrating their practical differences and applications.
Computer scienceMathematics
Audience: general audience
Basic Notions and Applied Topology Seminar
| Organizer: | Julian Brüggemann |
| Curator: | John Rick* |
| *contact for this listing |
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