This repository contains Deep Learning based articles , paper and repositories for Recommender Systems

A recommender engine built for a Bay Area online dating website to maximize the successful matches by introducing hybrid recommender system and reverse match technique.

Full-stack hybrid book recommendation system combining Collaborative Filtering and Content-Based Filtering with weighted hybrid scoring, modular data pipelines, and model persistence. Deployed via Flask with responsive HTML/CSS UI and integrated CI/CD for production-ready, scalable, and interactive recommendations.

This repository contains the core model we called "Collaborative filtering enhanced Content-based Filtering" published in our UMUAI article "Movie Genome: Alleviating New Item Cold Start in Movie Recommendation"

Hotel Recommendation system based on Content, Collaborative, Social Network Based Systems

A python based hybrid recommendation system built from scratch

This is the source code for my MSc thesis on Hybrid Recommendation Systems using Neural Networks.

A small neural net to recommend movies to the user

A implementation in Scala of CF, Content Based, Sequential and hybrid recommender systems for Spark

The goal of this project is to implement a Hybrid Recommender System that combines item-based and user-based recommendation methods to provide movie recommendations for a specific user. The system aims to offer a total of 10 movie recommendations by using both methods.

An AI-native database designed for LLM applications, offering lightning-fast hybrid search across dense vectors, sparse vectors, multi-vector tensors, and full-text data.

Repository related to the project of the Data Mining graduate course of University of Trento, academic year 2022/2023.

Ohara bookshelf is a smart books recommendation platform using machine learning algorithms and neural network.

Sistema de Recomendação Híbrido desenvolvido no formato de WebService RESTful utilizando Spring Boot

Trend Fitness is a web application dedicated to providing professional fitness advice which will include a range from fitness plans to diet plans catered to every individual needs. I believe that my web application will embark on a transformative journey towards a healthier lifestyle.

The assignment comprises two main tasks: implementing LSH to identify similar businesses based on user ratings and developing various collaborative filtering recommendation systems to predict user ratings for businesses.

A Spotify Music Recommender System that uses a hybrid recommendation approach (combining content-based scoring with track popularity) to suggest personalized music tracks through a Streamlit-based interactive app.