https://github.com/aianytime/recommendation_system_implementation

Complete concepts behind implementing a Recommendation System using Association Rules, Collaborative Filtering, and Matrix Factorization.
https://github.com/aianytime/recommendation_system_implementation

collaborative-filtering data-science machine-learning matrix-factorization python recommender-system scikit-learn

Last synced: about 2 months ago
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Complete concepts behind implementing a Recommendation System using Association Rules, Collaborative Filtering, and Matrix Factorization.

• Host: GitHub
• URL: https://github.com/aianytime/recommendation_system_implementation
• Owner: AIAnytime
• License: mit
• Created: 2021-02-15T06:32:42.000Z (over 5 years ago)
• Default Branch: main
• Last Pushed: 2021-05-02T06:44:33.000Z (about 5 years ago)
• Last Synced: 2025-05-20T10:45:21.939Z (about 1 year ago)
• Topics: collaborative-filtering, data-science, machine-learning, matrix-factorization, python, recommender-system, scikit-learn
• Language: HTML
• Homepage:
• Size: 631 KB
• Stars: 3
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Recommendation_System

Complete concepts behind implementing a Recommendation System using Association Rules, Collaborative Filtering, Matrix factorization, and Hybrid models.