Neural Collaborative Filtering implementation in Swift for TensorFlow
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Updated
Mar 20, 2020 - Jupyter Notebook
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)
Neural collaborative filtering recommendation system on Movie lens 100k dataset
Implementation of NCF paper (https://arxiv.org/abs/1708.05031). Optional, you can use item and user features to reach higher scores
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.
Neural Collaborative Filtering Revised
Neural recommendation models in Python, using Tensorflow 2.0 & Keras.
SER for emotions recognition - CNN & NCF for recommendations
Collaborative Filtering With User or Item Feature
This is the source code for my MSc thesis on Hybrid Recommendation Systems using Neural Networks.
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
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 Collaborative Filtering with MovieLens in pytorch
A collection of diverse recommendation system projects, spanning collaborative filtering, content-based methods, and hybrid approaches.
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