usearch
Fast Open-Source Search & Clustering engine × for Vectors & Arbitrary Objects × in C++, C, Python, JavaScript, Rust, Java, Objective-C, Swift, C#, GoLang, and Wolfram 🔍
WSKNN - Weighted Session-based K-NN recommender system
WSKNN - Weighted Session-based K-NN recommender system - Published in JOSS (2023)
tensorflow-recommenders
TensorFlow Recommenders is a library for building recommender system models using TensorFlow.
catalyst
Accelerated deep learning R&D
sasrec.pytorch
PyTorch(1.6+) implementation of https://github.com/kang205/SASRec
weaviate
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
persia
High performance distributed framework for training deep learning recommendation models based on PyTorch.
recommenderlab
recommenderlab - Lab for Developing and Testing Recommender Algorithms - R package
rsparse
Fast and accurate machine learning on sparse matrices - matrix factorizations, regression, classification, top-N recommendations.
recsys-examples
Examples for Recommenders - easy to train and deploy on accelerated infrastructure.
bars
BARS: Towards Open Benchmarking for Recommender Systems https://openbenchmark.github.io/BARS
https://github.com/google-research/recsim
A Configurable Recommender Systems Simulation Platform
https://github.com/alibaba/alink
Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
https://github.com/google-research/recsim_ng
RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems
https://github.com/aarnasi/ml-scikit-learn
Traditional machine learning (ML) demonstrations for data analysis and predictive modeling.
https://github.com/astrazeneca/skywalkr-graph-features
Example notebooks that illustrate how to generate knowledge-based features. Features can be used in a variety of ML models, including recommender systems.
xbrecs
XBRecs is an explainable book recommender system which bases its recommendations on book descriptions manipulated using NLP techniques.
hybridbackend
A high-performance framework for training wide-and-deep recommender systems on heterogeneous cluster
https://github.com/andrebola/contrastive-mir-learning
This repo contains the code to reproduce the paper: "Enriched Music Representations with Multiple Cross-modal Contrastive Learning"
accelerating-recsys-training
Accelerating Recommender model training by leveraging popular choices -- VLDB 2022
optimisingbeyondaccuracy
Keras-based neural recommender system trained on the MIND dataset, using attention mechanisms and differentiable loss regularisation to balance accuracy, diversity, and novelty.
fashion-image-recommender
Image Recommendation via similarity retrieval through deep learning
eosc-recommender-metrics
A framework for evaluating Recommender Systems (EOSC Recommender System)
tag-recom
Data and source code of the paper "A Content-Based Model for Tag Recommendation in Software Information Sites."
https://github.com/aksw/frankgraphbench
The FranKGraphBench is a Framework to allow KG Aware RSs to be benchmarked in a reproducible and easy to implement manner. It was first created on Google Summer of Code 2023 for Data Integration between DBpedia and some standard RS datasets in a reproducible framework.
predicting-missing-pairwise-preferences-in-gdm
Predicting missing pairwise preferences from similarity features in group decision making and group recommendation system