This repository contains exercises, code, and resources for the Machine Learning for Time Series (MLTS) course at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). The course covers various techniques for analyzing and modeling time series data.
Machine Learning and Data Analytics Lab (MaDLab)
Department Artificial Intelligence in Biomedical Engineering (AIBE)
Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
The exercises are structured into six topics, with each topic beeing discussed over two sessions. First you will get a theoretical overview of the topic and a Jupiter Notebook with practical tasks. In the following session, we will discuss and solve the tasks. On StudOn, you will find the slides for the different topics, while the tasks as well as the solutions will be uploaded to this repository.
You can find the nessesary requirements in the requirements.txt files of each exercise folder.
# Clone the repo
git clone https://github.com/username/mlts-exercises.git
cd mlts-exercises
# Setup a virtual environment
# Install your dependencies
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