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Implemented sparse matrix completion algorithms and principles of recommender system to develop a predictive user-movie rating model.

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Jeff09/Movie-Recommender-System

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Movie-Recommender-System

In order execute the program, you need to do the following steps:

  1. This program is executed under python 2.7 environment and requires numpy and pandas libraries installed
  2. You need to extract ml-100k.zip into local file
  3. For user-based and item-based collaborative filter models, you need to input the following orders into the prompt command: --python infor_cf.py
  4. For user-based and item-based KNN algorithm, you need to input the following orders into the prompt command: --python KNN.py
  5. For latent factor model, you need to input the following orders into the prompt command: --python matrix_factorizaiton.py

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Implemented sparse matrix completion algorithms and principles of recommender system to develop a predictive user-movie rating model.

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