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An application of collaborative filtering (PySpark, ALS, MLlib) and content-based filtering algorithms (NLP) to build a personalized song recommender based on listeners' behavior and a lyric-based song recommender for new users.

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Song Recommendation Systems

Inspired by Discover Weekly playlist from Spotify, we, a geek group of music lovers, explored recommendation algorithms and built two personalized song recommenders. One gives users a playlist based on their listening history, and the other one recommends song based on lyric.
The RS Code folder contains 3 jupyter notebooks for collaborative filtering recommendation system, lyric-based recommendation system, and lyric visualization.
The Data Preprocessing folder contains 2 jupyter notebook for data extracting and aggregration.
The detailed write-up can be found at https://bigforehead.github.io/

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An application of collaborative filtering (PySpark, ALS, MLlib) and content-based filtering algorithms (NLP) to build a personalized song recommender based on listeners' behavior and a lyric-based song recommender for new users.

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