Music Recommendations Using Machine Learning

Initial setup

1. Install Python 3.6. Preferably not 3.7. There could be some compatability issues if you use 3.7.
2. Execute pip install -r requirements.txt to install required Python packages. Optional: Use virtualenv to create a project-specific environment for the packages: https://virtualenv.pypa.io/en/stable/. This is recommended to keep package dependencies local to the project instead of being global on your machine.
3. If you want to use spotipy to fetch features for your own playlists, you have to install the additional package called spotipy (pip install spotipy) and create a secrets.py file, in spotipy_tools folder, containing CLIENT_ID and CLIENT_SECRET constants (to use with Spotify API). Otherwise you can just construct the dataset from the playlists in the repo (dataset_config.py).

Note: The file names of downloaded playlists (pkl files) are parsed from playlist names and Windows users may have issues with these. If that is the case, just rename *.pkl file or skip file.

Spotify Web API

https://developer.spotify.com/web-api/

Get CLIENT_ID and CLIENT_SECRET by registering at https://developer.spotify.com/my-applications/

Spotipy

Python package which implements Spotify Web API, which is used to extract features: http://spotipy.readthedocs.io/en/latest/

Framework Documentation

• sklearn: http://scikit-learn.org/stable/documentation.html
• keras: https://keras.io/