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3) Mood Track Visualiser - Develop a machine learning model that predicts the mood or energy level of a song based on its audio features. Allow users to input a track ID, and the model will predict the mood or possibly visualise energy level in the form of a chart.
4) Music Timeline Generator - Generates a timeline of a user's music listening history, use Spotify API to retrieve the user's listening history and then analyse the data to identify significant milestones such as discovery of new genres, favorite artists, or the release of specific albums.
1) Top 100 Playlist Generator - Create a playlist with your top 100 songs in the last X number of months. https://developer.spotify.com/documentation/web-api/reference/get-users-top-artists-and-tracks https://developer.spotify.com/documentation/web-api/reference/create-playlist
2) Playlist Anomaly Detector - Implement anomaly detection algorithms to identify unusual patterns in a user's playlist. This could include sudden shifts in genre, tempo, or the introduction of new artists. Visualise and alert users of these anomalies. https://developer.spotify.com/documentation/web-api/reference/get-a-list-of-current-users-playlists
3) Mood Track Visualiser - Develop a machine learning model that predicts the mood or energy level of a song based on its audio features. Allow users to input a track ID, and the model will predict the mood or possibly visualise energy level in the form of a chart.
4) Music Timeline Generator - Generates a timeline of a user's music listening history, use Spotify API to retrieve the user's listening history and then analyse the data to identify significant milestones such as discovery of new genres, favorite artists, or the release of specific albums.