Spotify ML Sorting and Song Recommendation Algorithm

I love music but since my taste varies so much and I am too lazy to make my own playlists I end up grouping all my songs in one giant 2000 song playlist. But when I'm in the mood for specific genres it can get annoying.
So to test out my Python skills I created a ML algorithm that uses numerous clustering techniques (e.g. Agglomerative Clustering, Affinity Propagation and Spectral Clustering) to split my songs into playlists based on features spotify has asigned them (e.g. danceability, loudness and rhythm).
After the data is cleaned and fitted the algorithms group the songs into playlist and their performance is based on how many songs of similar genre are grouped.
The clusters are then automatically converted into playlists using the Spotify API.
I then furthered this project by using Unsupervised Learning to create a song recommendation system, that would recommend similar songs and gain feedback based on whether I liked it or not.