a recommender engine node-js package for general use and easy to integrate.
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Updated
Jan 5, 2022 - TypeScript
a recommender engine node-js package for general use and easy to integrate.
Recommender for suggesting letter writers 👍
An Elective Courses Recommender System
🚀 End to End Movie Recommendation system built with NextJS, Flask, MySQL, TailwindCSS and AWS 🛸. Performs 📝 Content based, Collaborative and Neural Collaborative recommendations. --> Ongoing project
Recomm.js is a javascript library used to build recommendation systems, using Content-Based Filtering System.
Web-based Movie Recommendation Engine based on Deep Learning.
Scientific Paper Recommendations And Search, Powered by Recombee
Explore a smarter way to shop online with this full-stack project built on the infrastructure of Google Cloud Platform (GCP) for RAG based e-commerce with LLM.
Facial Recognition and Recommendation System based Web application
Web front-end of the advisor.ai project, an article search and recommendation platform focused on promoting collaboration between researchers using AI.
Implementation of Microsoft's Matchbox Recommender trained on MovieLens dataset used in simple React web application to provide movie recommendations.
Fullstack movie data application where users can find information about different movies with reviews and ratings and get recommendations. Movie data is fetched from TMDB API
AI-powered game recommendation system using KNN and collaborative filtering, with Flask and C# APIs and an Angular frontend
A movie recommendation platform powered by the Gorse recommender system service and integrated with the Typesense search engine. This dynamic system continually updates its database with the latest movies from TMDB API, ensuring users receive tailored suggestions based on their preferences.
A social book review and discovery platform with real-time, personalized recommendations using FAISS and LDA. Built with Next.js, Tailwind CSS, and TypeScript.
TripBuddy is a travel recommendation system that helps users find places based on real-time data from Google Maps API. The application uses Firebase for authentication and integrates with a backend API deployed on Render to fetch and display place recommendations.
Plant disease detection mobile app
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