Lernergebnisse
On successful completion of the module, students will be able to
- use Python and/or R libraries relevant to audio, music information retrieval, music metadata retrieval, and machine learning (such as numpy, sklearn, torch, pandas, etc.);
- understand machine learning theory and apply machine learning methods in practice;
- analyse audio, music, lyrics and music metadata using statistical and machine learning methods;
- implement audio and music ML applications;
- set up and optimise machine learning workflows, pipelines and lifecycles;
- understand and implement research in audio and music using machine learning;
- evaluate the success and validity of machine learning models using relevant objective metrics and subjective tests;
- learn how to interpret and communicate machine learning results in science as well as for laypeople;
- critically examine the impact of data acquisition and machine learning on artists, musicians, listeners, cultural scenes, the environment and society.
