lightfm

MelodyMind offers personalized music recommendations, from a real-time Last.fm API-powered app to an advanced hybrid system combining content-based and collaborative filtering with LightFM.

store my personal project

python package to help preparing Dataframes (csv ... ) for LightFM module for easy Training

An realtime recommendation system supporting online updates

Pre-train Embedding in LightFM Recommender System Framework

This example uses the lightfm recommender system library to train a hybrid content-based + collaborative algorithm that uses the WARP loss function on the movielens dataset

Built a hybrid recommendation system with LightFM library and customised loss functions to optimize performance on retail data."

A hybrid recommender system for suggesting CDN (content delivery network) providers to various websites

with Kaggle datasets

A full-stack recommender system built to provide personalized and content-based recommendations- currently for movies but in progess

Implicit Event Based Recommendation Engine for Ecommerce

✨ Recommendation Systems Using Diverse Techniques ✨

Learn Data Science with Python

A recommendation system that recommends artists to users.

Recommendation engine with a .97 AUC achieved using clustering techniques to create user features. Data represents Olist marketplace transactions and was retrieved from kaggle.com.

WordPress Posts Recommend System based on Collaborative Filtering.

✨ Recommendation Systems Using Diverse Techniques ✨

Рекомендательные системы

This project is focused on building a movie recommendation system using the MovieLens dataset. The system leverages several machine learning techniques to provide personalized movie recommendations based on user preferences and past behaviors.

Movie recommender exploring content-based, collaborative (LightFM), and hybrid filtering on TMDB + MovieLens — with PostgreSQL/SQLite ETL and offline evaluation