Recommender Learning with Tensorflow2.x

A pytorch implementation of He et al. "Neural Collaborative Filtering" at WWW'17

NeuCharFramework Template Project

A .NET Standard library containing models and functionality for managing, organizing, and sending a collection of HTTP requests using the Nightingale Collection Format. This library is the heart of Nightingale REST Client on Windows 10.

Federated Neural Collaborative Filtering (FedNCF). Neural Collaborative Filtering utilizes the flexibility, complexity, and non-linearity of Neural Network to build a recommender system. Aim to federate this recommendation system.

Library/Driver for NXP PN7150 NFC device

plugin de adaptación de FacturaScripts a República Dominicana

Neural Collaborative Filtering with MXNet

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

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

STAT4609 project, in collaboration with @jevrii and @kellycyy. Git commit authors do not necessarily represent the actual author.

TypeScript library for utilities relevant to the Dominican Republic, such as Cedula, RNC, and NCF validation and formatting.

A parser for retrieving data from automotive Node Configuration Files (NCF)

[제 12회 투빅스 컨퍼런스] 겜플리 - 이미지・텍스트 기반 나만의 추천 게임플레이리스트

NCF Recommender System (Pytorch)

A collection of Movie Recommender System models developed using PyTorch

DGII-Utils es un paquete de herramientas diseñado para simplificar la interacción con las aplicaciones web de la Dirección General de Impuestos Internos (DGII) en la República Dominicana. Este paquete incluye funciones para validar formatos fiscales como RNCs, cédulas, y comprobantes fiscales.

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

This repository presents a News Recommendation System using Azure Data Factory, Azure Databricks, and Azure Data Lake to create a data pipeline for ML models. It uses BERT for content-based filtering, Neural Collaborative Filtering for user behaviors, and a hybrid model that combines both to enhance news recommendations.