recommeder-systems

The detialed codes written in Matlab R2015b version in paper "RNR: A Generic Bayesian-based Framework for Enhancing Top-N Recommender Systems "

A developing review-awared recommender system with pytorch

In this Repository, A simple content-based book recommendation system is implemented. A representation vector is built with a TF-IDF vector of the Authors name concatenated with the title of the book.

[BIBM 2025] Source code for "CafeMed: Causal Attention Fusion Enhanced Medication Recommendation".

Rating System supported by Solidity smart contracts

Python and SQL projects all the way from simple classification, to deep learning

Machine Learning - Standford University (Coursera)

End-to-end course recommender system project.

CSE 593

This repository is about my semester project related to the course Big Data Analytics. I developed a recommendation system engine based on Hotel Reviews Dataset. Read more about the implementation in markdown file.

Fashion-Recommendation-System-using-Image-Features is a Streamlit-Python app leveraging Deep Learning and Machine Learning to provide personalized fashion recommendations through image analysis.

1st place solution for the Recommender Systems challenge at Politecnico di Milano 2025/26

BloomSage ML Component

Content-Based Anime Recommendation System

Introduction to Recommender Systems: Non-Personalized and Content-Based University of Minnesota

Recipe Assistant is a command-line application that helps users generate or search for recipes using simple ingredient keywords. It supports local recipe generation via Ollama and real recipe search using Google Custom Search, with smart keyword preprocessing, taste preference detection, and secure API key management.

Microsoft Engage program 2022

Bachelor's thesis titled "Knowledge graph enhanced recommender systems".

Combination of the sentiment analysis and the recommendation system

This repository hosts the code and the settings for the paper "Modular Debiasing of Latent User Representations in Prototype-based Recommender Systems" by Alessandro B. Melchiorre, Shahed Masoudian, Deepak Kumar, and Markus Schedl at ECML-PKDD'24.