dima806/music_genres_classification

Music genre classification is a fundamental and versatile application in many various domains. Some possible use cases for music genre classification include:

• music recommendation systems;
• content organization and discovery;
• radio broadcasting and programming;
• music licensing and copyright management;
• music analysis and research;
• content tagging and metadata enrichment;
• audio identification and copyright protection;
• music production and creativity;
• healthcare and therapy;
• entertainment and gaming.

The model is trained based on publicly available dataset of labeled music data — GTZAN Dataset — that contains 1000 sample 30-second audio files evenly split among 10 genres:

• blues;
• classical;
• country;
• disco;
• hip-hop;
• jazz;
• metal;
• pop;
• reggae;
• rock.

The final code is available as a Kaggle notebook. See also my Medium article for more details.