Neural collaborative filtering recommendation system on Movie lens 100k dataset
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Updated
May 28, 2024 - Jupyter Notebook
Neural collaborative filtering recommendation system on Movie lens 100k dataset
Factorization Machine models in PyTorch
A Julia implementation of three different recommender systems based on the concept of Neural Collaborative Filtering.
Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
A collection of diverse recommendation system projects, spanning collaborative filtering, content-based methods, and hybrid approaches.
A Deep Learning Based Context-Aware Recommendation Library
implementation of federated neural collaborative filtering algorithm
PyTorch Implemenation for Neural Graph Collaborative Filtering
Neural recommendation models in Python, using Tensorflow 2.0 & Keras.
Restaurant Recommender System: Neural Collaborative Filtering
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.
Official code for "DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation" (TPAMI2022) and "Are We Evaluating Rigorously? Benchmarking Recommendation for Reproducible Evaluation and Fair Comparison" (RecSys2020)
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 recommender system implementation in TensorFlow.
Collaborative Filtering With User or Item Feature
This is the source code for my MSc thesis on Hybrid Recommendation Systems using Neural Networks.
Neural Collaborative Filtering with MovieLens in pytorch
Seoul Tourism Recommendation System
Neural Collaborative Filtering with MovieLens dataset(WWW, 2017)
A pytorch implementation of He et al. "Neural Collaborative Filtering" at WWW'17
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