We believe that people deserve unaquitted, fair access to any and all musical recommendations. Because of this belief, we created our app, "Spotify Recommender".
Product Vision Document: https://docs.google.com/document/d/1m9od5rn3VZYmwmIIQ6vmAkmwYi_tJN9fRVn2lmwwA-o/edit?usp=sharing
Link to Heroku App where our application lives: https://spotify-predictor01.herokuapp.com/
Our application uses a KNN (k-nearest neighbors model), to create our suggestions to our users. Users need only input their favorite song title and the application will return the top 5 songs that have the highest correlation to the input song.
This application takes advantage of Flask, SQLAlchemy, PostGreSQL, and Python. We have included a requirements.txt in our GitHub Repo that includes any dependancies that may be needed for this library.
This project runs off the MIT license
Our application is available via Heroku at the following link:
This application should require no additional items or downloads from the users.
This app was a collaborative effort between the following individuals:
Alexander Lucchesi: Dan Ferber: Luke Sislowski: