This project proposes the development of a module that uses Machine Learning to classify correctly the audio-based relative data which is extracted from music tracks. Python’s related Machine Learning (ML) library, scikit-learn, is used for the training of the data and the predictions of the classification results.

This work replaces/reproduces the existing ML classification problem procedure that follows the gaia library with a new ML model infrastructure that uses the Python library, scikit-learn. This new infrastructure is built in high-level modeling, it reproduces classification process with the SVM model, and can be easily extended with other Machine Learning and Deep learning models that can be then compared between each other or even combined.


Pantelis Tzamalis


  • Alastair