SER for emotions recognition - CNN & NCF for recommendations

Neural Collaborative Filtering implementation in Swift for TensorFlow

Neural Collaborative Filtering with MovieLens dataset(WWW, 2017)

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.

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.

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.

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.

A Julia implementation of three different recommender systems based on the concept of Neural Collaborative Filtering.

分别使用传统方法（KNN，SVD，NMF等）和深度方法（NCF）进行推荐系统的评分预测。Traditional methods (KNN, SVD, NMF, etc.) and depth method (NCF) were used to predict rating of the recommendation system.

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

Seoul Tourism Recommendation System

A collection of Movie Recommender System models developed using PyTorch

Collaborative Filtering With User or Item Feature

Neural Collaborative Filtering Revised