StanislavKo28/music_moods_classification

Music mood classification is a fundamental and versatile application in many various domains. Some possible use cases for music mood 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 — HWNAS Dataset — that contains 6930 sample 30-second audio files evenly split among 14 moods:

• —angry;
• —dark;
• —energetic;
• —epic;
• —euphoric;
• —happy;
• —mysterious;
• —relaxing;
• —romantic;
• —sad;
• —scary;
• —glamorous;
• —uplifting;
• —sentimental.

Kaggle notebooks:

• —Training - Kaggle notebook;
• —Inference - Kaggle notebook.