Fast Python Collaborative Filtering for Implicit Feedback Datasets
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Updated
May 27, 2024 - Python
Fast Python Collaborative Filtering for Implicit Feedback Datasets
A unified, comprehensive and efficient recommendation library
A deep matching model library for recommendations & advertising. It's easy to train models and to export representation vectors which can be used for ANN search.
Neural Collaborative Filtering
Deep learning for recommender systems
An Open-source Toolkit for Deep Learning based Recommendation with Tensorflow.
Next RecSys Library
Factorization Machine models in PyTorch
This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.
A Comparative Framework for Multimodal Recommender Systems
Neural Graph Collaborative Filtering, SIGIR2019
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)
A developing recommender system in tensorflow2. Algorithm: UserCF, ItemCF, LFM, SLIM, GMF, MLP, NeuMF, FM, DeepFM, MKR, RippleNet, KGCN and so on.
[WSDM'2024 Oral] "SSLRec: A Self-Supervised Learning Framework for Recommendation"
Book recommender system using collaborative filtering based on Spark
BARS: Towards Open Benchmarking for Recommender Systems https://openbenchmark.github.io/BARS
Versatile End-to-End Recommender System
PyTorch Implementations For A Series Of Deep Learning-Based Recommendation Models
Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
Recommender system and evaluation framework for top-n recommendations tasks that respects polarity of feedbacks. Fast, flexible and easy to use. Written in python, boosted by scientific python stack.
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