SER for emotions recognition - CNN & NCF for recommendations

This project it's a movie recommendation engine composed of a custom NCF model to predict user preferences and generate personalized recommendations for large-scale user-item interaction data.

Restaurant Recommender System: Neural Collaborative Filtering

Neural collaborative filtering recommendation system on Movie lens 100k dataset

A Movie Recommendator built using Neural Collaborative Filtering

Book recommendation system and reader rating analysis.

A collection of diverse recommendation system projects, spanning collaborative filtering, content-based methods, and hybrid approaches.

2020 Capstone Design

Seoul Tourism Recommendation System

Collaborative Filtering With User or Item Feature

Neural Collaborative Filtering Revised

Neural Collaborative Filtering implementation in Swift for TensorFlow

PyTorch Implementation for J-NCF (ACM Transactions on Information Systems, 2019)

This application focuses on recommending music artists using NCF. The dataset, HetRec 2011 Last.fm, includes user-artist interactions, friend relationships, and tagging information for 1,892 users and 17,632 artists. The model predicts top artist recommendations for users, incorporating social and listening behavior data to enhance personalization.

Implementation of NCF paper (https://arxiv.org/abs/1708.05031). Optional, you can use item and user features to reach higher scores

Anime Recommender System with various recommender system algorithms implemented in python

Implementation of paper Neural Collaborative Filtering in PyTorch.

The repository consists of a recommendation engine that suggests movies to the users based on the genre and ratings previously received. Under the hood, a neural collaborative filtering technique has been implemented

A collection of Movie Recommender System models developed using PyTorch