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Exploring different recommendation models on MovieLens data

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MovieReccommenderModels

Implementation of models was inspired from the resources provided in this course: https://www.udemy.com/building-recommender-systems-with-machine-learning-and-ai/

Code distribution:

  • EDA, Content-Recommendation: Sai
  • User-User CF, Item-item CF, Results: Keng, Andreas
  • Matrix SVD, Debugging, Refactoring: Yifei, Andreas

Instructions:

  • Install the required libraries listed in pip3req.txt using pip3

  • Run KNNRecs.py for Content Recommendation, SVD results

  • Run CF.py for collaborative filtering algorithms

  • change testSubject from User 75 to other users at line 212 of evaluator.py

    def SampleTopNRecs(self, ml, testSubject=75, k=10):

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Exploring different recommendation models on MovieLens data

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