This repository contains the machine learning part of the project especially the used algorithms for the recommendation system

Building powerful and personalized, recommendation engines with Python

The "Music Recommender System using Spotify API" project aims to create a personalized music recommendation system for users based on their listening preferences and behavior. By leveraging the Spotify API, we can access a vast collection of music data, including tracks, artists, genres, and user playlists.

Repository of the python scripts for the CS competition held in Kaggle obtaining the 4th place

The project is based on a Hybrid recommendation engine that uses both Collaborative as well as Content based filtering methods to suggest streamers to the online users based on the type content they consume.

Explore the Hybrid Recommender System on E-commerce Data repository! This GitHub project showcases a solution for building a hybrid recommender system. Dive into the code, discover innovative approaches, and enhance your understanding of creating effective recommendation systems tailored for E-commerce Data.

A hybrid group recommendation system for film and TV content using Letterboxd profile data

EDA, Pre-processing, 6 Recommendation Systems Techniques: * Popularity-Based, * Cosine Similarity Collaborative Filtering, * Matrix Factorization Collaborative Filtering, * Clustering, * Content-Based Filtering, * Hybrid Recommendation System.

Recommendation Systems with mathematical modelling

Amar deep architectures for hybrid recommenders with GNNs

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.

A movie recommender application

Content, Collaborative, and Hybrid Movie recommendation system

Hybrid Recommender System for Computer Science Papers | Master's Thesis Project 2023

Hybrid recommendation system using LightFM library and different loss functions on retail data.

Create a hybrid recommendation system to suggest the most relevant movies for a user

USC DSCI 553 - Foundations & Applications of Data Mining - Spring 2024 - Prof. Wei-Min Shen

This is an ecommerce recommendation system that is measured with weighted user rating and content cosine similarity.