Deep Learning (Part 2)
Jakub Malinowski (Dioscuri Centre in Topological Data Analysis)
| Mon Mar 9, 11:30-13:30 (2 months from now) | |
| Lecture held in Room 1 at the IMPAS, Room 1.14 at the Institute of Informatics (University of Gdańsk). |
Abstract: The second session expands on the foundations by covering more advanced deep-learning techniques and their applications. We will examine methods such as dropout learning, network tuning strategies, and architectural choices that influence model performance. The talk will show how deep learning can tackle complex tasks in domains like image recognition, text classification, or other high-dimensional prediction problems.
Computer scienceMathematics
Audience: general audience
Basic Notions and Applied Topology Seminar
| Organizer: | Julian Brüggemann |
| Curator: | John Rick* |
| *contact for this listing |
Export talk to