Introduction to Scientific Machine Learning for Engineers (MW2435)
Course 0000002392 in WS 2022/3
General Data
| Course Type | lecture |
|---|---|
| Semester Weekly Hours | 2 SWS |
| Organisational Unit | Chair of Aerodynamics and Fluid mechanics (Prof. Adams) |
| Lecturers |
Nikolaus Adams Assistants: Ludger Pähler Artur Petrov Toshev |
| Dates |
Mon, 15:00–16:30, ZEI 0001 |
Assignment to Modules
-
MW2435: Wissenschaftliches Maschinelles Lernen für Ingenieure / Introduction to Scientific Machine Learning for Engineers
This module is included in the following catalogs:- Focus Area Imaging in M.Sc. Biomedical Engineering and Medical Physics
Further Information
Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.
| additional remarks | This course presents the fundamentals of machine learning building on a basic understanding of linear algebra and the axiomatic description of probability theory. Starting with supervised learning basic regression approaches are being discussed, culminating in generalized linear models. Starting with support vector machines various kernel approaches such as Gaussian processes are then covered. We subsequently move on to the general class of neural network methods, their training via backpropagation, bias vs. variance trade-offs, regularization and modern classes of neural networks. The classes covered in this course are recurrent neural networks, convolutional neural networks, generative adversarial networks, and the more modern transformer networks. The course subsequently culminates in an introduction to variational inference, autoencoders and principal component analysis. The content is subject to change based on progress during the semester. |
|---|---|
| Links |
E-Learning course (e. g. Moodle) Additional information TUMonline entry |
Equivalent Courses (e. g. in other semesters)
| Semester | Title | Lecturers | Dates |
|---|---|---|---|
| WS 2021/2 | Introduction to Scientific Machine Learning for Engineers (MW2435) | ||
| WS 2020/1 | Introduction to Scientific Machine Learning for Engineers (MW2435) | Adams, N. Pähler, L. |
Thu, 09:30–11:00 |