Tool for simplifying to perform experiments with collaborative filtering models
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Updated
Oct 14, 2020 - Python
Tool for simplifying to perform experiments with collaborative filtering models
The is a course project, a within-class kaggle competition targeting to recommend the courses to the potential buyer.
RecAnthology is a hybrid recommendation system for books, movies, and TV shows that combines content-based modeling and collaborative filtering with adaptive weighting, cold-start handling, and offline evaluation metrics to deliver measurable, personalized recommendations.
This project builds a scalable recommendation system inspired by Netflix, leveraging collaborative filtering and deep learning techniques to predict user preferences. It focuses on large-scale data processing, model training, and performance evaluation for personalized content recommendations.
Noice-inspired hybrid audio recommendation system using public catalog-style metadata and synthetic listening events.
Benchmarks of collaborative filtering techniques and optimizing K-NN and SVD for recommendation accuracy
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