Movie Website built on python Django framework; Uses Content Based Predictive Model approach to predict similar movies based on the contents/genres similarities

Collaborative Filtering NN and CNN based recommender implemented with MXNet

Recommendation System for Amazon Alexa E-Commerce Application

3rd Year: 1st - 92. A Novel Context Aware Restaurant Recommender System Using Content-Boosted Collaborative Filtering (CACBCF).

Repository for the Recommender Systems Challenge 2020/2021 @ PoliMi

Recommender Service (Gợi ý các bài viết phù hợp với người dùng) cho ứng dụng "Quản lý học tập thông minh" - Đồ án môn học "Kiến trúc và thiết kế trong phát triển ứng dụng phần mềm"

WP3 - Recommendation of Prioritized Requirements

Machine Learning Music Recommendation System: Hybrid Approach (Content & SVD) with Flask

A simple books recommender system that provides the functionality to ask for books recommendations or search for them using various options.

Anime recommender system for Anilist user profiles and individual titles

An eCommerce website developed in the Django web framework. It implements a content-based filtering recommendation system based on the user usage history, user profile and item profile.

We create movie recommendation system through demographic filtering, content-based filtering, collaborative filtering, and hybrid engine.

A content-based Restaurant Recommendation System using TF-IDF and cosine similarity. Built with Python, enhanced with search & rating features, and deployed via Streamlit.

Repositório do artigo: http://seer.upf.br/index.php/rbca/article/view/10047

Recommendation Systems thesis. This repository contains the development of the evaluation of three recommendations system methods: Collaborative Filtering, Content Based and Hybrid.

Flight Booking Ticket (name: CaVi)

Recommender and Chatbot Systems

Coursework solutions for a 3rd year Computer Science module on Recommender Systems @ Durham University. Aims to use machine learning methods to recommend films.

A news recommendation system implemented on a hybrid combination of collaboration and content-based filtering along with a diversity re-ranking function

A simple movie recommender system that uses two main approaches to make recommendations: Content-based algorithm and Collaborative filtering algorithm (User-based).