This project implements an Item-Based Collaborative Filtering book recommendation system using K-Nearest Neighbors (KNN). Books are recommended based on similarity in user rating patterns rather than content information.
Recommendation App for Books and Manga: MANGOLEAF
Streamlit Restaurant Recommender
A Python-based hybrid book recommendation system that combines content-based and collaborative filtering techniques. Utilizes the Book-Crossing dataset for personalized recommendations.
A C++ project that predicts movie ratings using Item-Based Collaborative Filtering (IBCF) with Cosine Similarity. Developed for CMP2003 at Bahçeşehir University.
Movie recommender system using collaborative filtering and Flask web app.
A memory-based collaborative filtering system that predicts movie ratings using user–user and item–item similarity.
Live web application demonstrating personalized recommendations for books and mangas implemented using collaborative filtering based recommender systems
Product recommendation system is a Machine learning based project which can be used to proivde personalized recommendations.
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