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A recommendation algorithm capable of accurately predicting how a user will rate a movie they have not yet viewed based on their historical preferences. The models and EDA are based on the 1M MOVIELENS dataset

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Alexa, what should I watch next?

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Problem Statement

Construct a recommendation algorithm capable of accurately predicting how a user will rate a movie they have not yet viewed based on their historical preferences. The models and EDA are based on the 1M MOVIELENS dataset

Approach

  • First glance at the raw data
  • Preparing data for better visualization
  • Exploratory data analysis
  • Memory handling
  • Building the models
    • Content based
    • Collaborative based
  • Conclusion
  • References

Project status

Link to project Trello board: https://trello.com/b/qnGPL8mN/unsupervised-sprint

Get in touch

If you would like to contribute to the repository please contact nicole.meinie@gmail.com

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A recommendation algorithm capable of accurately predicting how a user will rate a movie they have not yet viewed based on their historical preferences. The models and EDA are based on the 1M MOVIELENS dataset

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