/Item-based-collaborative-filtering

This project utilizes PySpark DataFrames and PySpark RDD to implement item-based collaborative filtering. By calculating cosine similarity scores or identifying movies with the highest number of shared viewers, the system recommends 10 similar movies for a given target movie that aligns users’ preferences.

Primary LanguageJupyter Notebook

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