https://github.com/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.
https://github.com/aninditaguha98/spotify-recommendation-system
collaborative-filtering content-based-recommendation knn-algorithm recommender-system
Last synced: 4 months ago
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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.
- Host: GitHub
- URL: https://github.com/aninditaguha98/spotify-recommendation-system
- Owner: AninditaGuha98
- Created: 2020-12-09T19:41:30.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2021-01-12T21:18:40.000Z (over 4 years ago)
- Last Synced: 2023-03-07T12:29:02.495Z (about 2 years ago)
- Topics: collaborative-filtering, content-based-recommendation, knn-algorithm, recommender-system
- Language: Jupyter Notebook
- Homepage:
- Size: 31.9 MB
- Stars: 5
- Watchers: 1
- Forks: 1
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Spotify-Recommendation-System
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