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Collaborative Filtering, SVD and CUR based Recommender Systems. Tested on the MovieLens ratings dataset.

License: MIT License

HTML 40.42% Python 59.58%
recommender-system collaborative-filtering svd cur

recommender-systems-movielens1m's Introduction

Recommender-Systems-MovieLens1M

Generates recommendations/ratings for the MovieLens 1M dataset. Three classical techniques -

  1. Collaborative filtering
  2. SVD
  3. CUR

How to run

  1. Ensure all files are in same directory with the dataset.
  2. Run gen_data.py
  3. Run any one of SVD.py/CUR.py/Colabs.py

Taking too long?

Drive Link for saved .npy files https://drive.google.com/drive/folders/1ryMAn52AFThYmepU_0S7tS_XWIu3MUSs?usp=sharing

Will help save time if you download these and save to your directory.

recommender-systems-movielens1m's People

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