Convolutional Neural Networks and Deep Learning in Physics
Dozent:innen: Univ.-Prof. Dr. Matthias SchottKurzname: Neural Networks
Kurs-Nr.: 08.128.614
Kurstyp: Vorlesung
Voraussetzungen / Organisatorisches
Grundkenntniss in Python.Empfohlene Literatur
- Einführung in Machine Learning mit Python: Praxiswissen Data Science Taschenbuch – 26. Juni 2017Inhalt
In the lecture we will learn about the basic concepts of convolutional neural networks as well as deep learning approaches. We will use those for various applications in physics, starting from high energy physics analysis over data-taking towards solving the Schrödinger Equation.Termine
| Datum (Wochentag) | Zeit | Ort |
|---|---|---|
| 15.04.2019 (Montag) | 08:00 - 10:00 | |
| 29.04.2019 (Montag) | 08:00 - 10:00 | |
| 06.05.2019 (Montag) | 08:00 - 10:00 | |
| 13.05.2019 (Montag) | 08:00 - 10:00 | |
| 20.05.2019 (Montag) | 08:00 - 10:00 | |
| 27.05.2019 (Montag) | 08:00 - 10:00 | 01 525 Seminarraum K |
| 03.06.2019 (Montag) | 08:00 - 10:00 | 01 525 Seminarraum K |
| 17.06.2019 (Montag) | 08:00 - 10:00 | 01 525 Seminarraum K |
| 24.06.2019 (Montag) | 08:00 - 10:00 | 01 525 Seminarraum K |
| 01.07.2019 (Montag) | 08:00 - 10:00 | 01 525 Seminarraum K |
| 08.07.2019 (Montag) | 08:00 - 10:00 | 01 525 Seminarraum K |