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Recommendation System algorithmic implementations of User-based and Item-based collaborative filtering on MovieLens 100k Data

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Recommendation Systems

This repo contains implementation of different algorithms in Collborative filtering for recommendation systems.

P2.ipynb is the implementation of the item-based top-N algorithm from Karypis, George. “Evaluation of Item-Based Top-N Recommendation Algorithms.” 2000, doi:10.21236/ada439546.

imp.R is the implementation of Item-Based Collaborative Filtering Recommendation Algorithms from Sarwar, Badrul, et al. “Item-Based Collaborative Filtering Recommendation Algorithms.” Proceedings of the Tenth International Conference on World Wide Web - WWW 01, 2001, doi:10.1145/371920.372071.

Link to Data: https://grouplens.org/datasets/movielens/100k/

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Recommendation System algorithmic implementations of User-based and Item-based collaborative filtering on MovieLens 100k Data

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