References: https://medium.com/@sumanadhikari/building-a-movie-recommendation-engine-using-scikit-learn-8dbb11c5aa4b https://towardsdatascience.com/various-implementations-of-collaborative-filtering-100385c6dfe0 https://github.com/codeheroku/Introduction-to-Machine-Learning/tree/master/Collaborative%20Filtering https://towardsdatascience.com/an-overview-of-several-recommendation-systems-f9f8afbf00ea https://github.com/nikitaa30/Recommender-Systems/blob/master/knn_recommender.py https://heartbeat.fritz.ai/recommender-systems-with-python-part-ii-collaborative-filtering-k-nearest-neighbors-algorithm-c8dcd5fd89b2 https://pankaj-tiwari2.medium.com/neighborhood-based-collaborative-filtering-in-python-using-surprise-fe9d5700cb58
AninditaGuha98/Spotify-Recommendation-System
Implemented and compared different recommendation systems for Spotify playlists for both artists and types of songs. Implemented popularity-based recommenders, content-based recommenders, and used the KNN algorithm for implementing collaborative filtering.
Jupyter Notebook