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GitHub / somjit101 / Netflix-Movie-Recommendation
A case study of the Netflix Prize solution where, given anonymous data of users and the ratings given to movies, the objective to provide recommendations to users for movies which they would like, based on their past activity and taste.
JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/somjit101%2FNetflix-Movie-Recommendation
Stars: 1
Forks: 0
Open Issues: 0
License: None
Language: Jupyter Notebook
Repo Size: 9.07 MB
Dependencies: pending
Created: almost 3 years ago
Updated: over 1 year ago
Last pushed: almost 3 years ago
Last synced: 11 months ago
Topics: boosting-algorithms, implicit-feedback, machine-learning, matrix-factorization, movie-recommendation, netflix, netflix-prize, recommendation-engine, recommendation-system, regression-models, surprise-library, svd, svd-factorization, svd-matrix-factorisation, svdpp, xgboost, xgboost-regression