/Spotify

This API created by Lambda Students uses an K-Nearest Neighbors algorithm that anaylzed our numerical features, which include categories such as danceability, loudness, tempo, etc. The K-NN Model then returned 10 songs that were within closest/similar vector space to the original song chosen by the user.

Primary LanguageJupyter NotebookMIT LicenseMIT

Spotify Song Suggestor Application

This API created by Lambda Students uses an K-Nearest Neighbors algorithm that anaylzed our numerical features, which include categories such as danceability, loudness, tempo, etc. The K-NN Model then returned 10 songs that were within closest/similar vector space to the original song chosen by the user.

Endpoint

Our organization(TT-69) deployed a Heroku App that can be found here (https://predictifyforspotify.herokuapp.com/).

Data

The K-Nearest Neighbors model was trained on data from Kaggle.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

Authors and Acknowledgment

API Engineering/Front-End Engineering: Victoria Debebe, Henry Mead, Drew Bordelon

Data Modeling: Lucas Petrus, Josiah McKinney

License

MIT