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)

Recommender System ⬩ Created a Neural Collaborative Filtering Recommender System to predict user engagement/interaction using movies from 1995 to 2020 in the MovieLens dataset.

Neural recommendation models in Python, using Tensorflow 2.0 & Keras.

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

Collaborative Filtering With User or Item Feature

Neural Collaborative Filtering Revised

Neural collaborative filtering recommendation system on Movie lens 100k dataset

Implementation of paper Neural Collaborative Filtering in PyTorch.

Anime Recommender System with various recommender system algorithms implemented in python

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

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

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.

Restaurant Recommender System: Neural Collaborative Filtering

This is the source code for my MSc thesis on Hybrid Recommendation Systems using Neural Networks.

Neural Collaborative Filtering with MovieLens in pytorch

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

implementation of federated neural collaborative filtering algorithm