Topic: "collaborative-filtering-based-recommendation"
Rishabhrv/Book-Reccomender-App
The Book Recommender System is a collaborative filtering-based approach that suggests personalized book recommendations based on user preferences and similarities. The system provides a user-friendly interface through Streamlit for an enhanced user experience.
Language: Jupyter Notebook - Size: 2.91 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 3 - Forks: 0
FarHard112/Spider-V1-Game-Recommender-System
AI-powered game recommendation system using KNN and collaborative filtering, with Flask and C# APIs and an Angular frontend
Language: TypeScript - Size: 491 KB - Last synced at: 2 months ago - Pushed at: 9 months ago - Stars: 1 - Forks: 0
danish1804/recommender-system
A collaborative filtering-based movie recommender system built using Python. Implements both user-user k-NN and matrix factorization techniques with evaluation metrics like RMSE for performance benchmarking.
Language: Jupyter Notebook - Size: 22.5 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
ArunR1408/Movie-Recommendation-Engine-R
An R-based engine to recommend movies using collaborative filtering.
Language: R - Size: 1.3 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 1
sharmeen-k/Movie-Recommender-System
A content-based system recommends movies to an input user based on the weighted genre score of a movie and a collaborative filtering system recommends movies liked by other users having a similar taste profile as the input user.
Language: Jupyter Notebook - Size: 39.1 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0
iamSobhan/book_recommendation_system
Book Recommendation System
Language: Jupyter Notebook - Size: 45.7 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
