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Applied Machine Learning for Engineers
Last Updated: 2026-02-05 15:41:35
Abstract
Introduction to the most frequently used methods of machine learning, including regression, classification, dimensionality reduction and selected topics of deep learning, including artificial neural networks, convolutional neural networks, recurrent neural networks and autoencoders. This lecture has a strong practical focus with programming sessions.
Objective
An understanding of the various tools within the machine learning landscape. Ability to select an appropriate method and to build, train and evaluate a model using Scikit-learn and Keras.
Content
Data preprocessing, regression, classification, dimensionality reduction, artificial neural networks, convolutional neural networks, recurrent neural networks, autoencoders.
Resources
Lecture Notes
Lecture notes will be distributed electronically.
General Information
- Language
- English
- Levels
- MSC
Examination
- Type
- session examination
- Mode
- oral 30 minutes
Registration & Places
- Max Places
- 40
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise | Applied Machine Learning for Engineers |
|
3 h weekly |
Offered In
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Energy, Flows and Processes (The courses listed in this category “Core Courses” are recommended. Alternative courses can be chosen in agreement with the tutor.)
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