Junction 17 - Partify
Queueing songs at a party is always a struggle. Our solution: generate a playlist automatically using machine learning based on the users favorite tracks and the mood of the party.
How it works
We analyzed songs labelled by their playlists titles to determine what metadata parameters determines the mood and feel of a song, from calm (lounge) to intense (club). For this we used a Support Vector Machine model.
react, spotify api, scikit/learn Using the Spotify API and the library
The Backend is built using Python and Flask library. The tracks are classified with a Support Vector Machine with regularization in SciKit Learn. Frontend wise we’ve used React and Redux. All the data is fetched using the Spotify API.
Setup
export SPOTIPY_CLIENT_ID='xxx'
export SPOTIPY_CLIENT_SECRET='yyy'
pip install flask sklearn spotipy # deps (see requirements.txt)
export FLASK_APP=src/main.py
flask run
License
Copyright Team D-0x10
(TBA)