Skip to content

A repo for my MSEE thesis project, "Feature extraction and machine learning techniques for musical genre determination" (California State University, Northridge; December 2017). This project is also hosted on ScholarWorks.

License

Notifications You must be signed in to change notification settings

rosydavis/rdavis_msee_project_csun2017

Repository files navigation

README

This repo contains the core Python code used for my masters project, "Feature Extraction and Machine Learning Techniques for Musical Genre Determination," for which I will be receiving a Masters of Science in Electrical Engineering from California State University, Northridge in December 2017. My advisor at CSUN is Dr. Xiyi Hang. My paper and this code is also hosted on ScholarWorks via the CSUN library.

My project relies heavily on the FMA dataset and the accompanying paper, "FMA: A Dataset for Music Analysis", by Michaël Defferrard, Kirell Benzi, Pierre Vandergheynst, and Xavier Bresson, though my code is adaptable to other datasets. All code in this repo is released under the terms of the MIT license.

About

A repo for my MSEE thesis project, "Feature extraction and machine learning techniques for musical genre determination" (California State University, Northridge; December 2017). This project is also hosted on ScholarWorks.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published