 RecSysDatasets
 RecSysDatasets 
 Recommender datasets
 A repository of public data sources for Recommender Systems.
This is a repository of public data sources for Recommender Systems (RS).
887 stars
 14 watching
 133 forks
 
Language: Python 
last commit: about 1 year ago   atomic-filesdatasetrecbolerecommendation-datasetsrecommendationsrecommender-system 
 Related projects:
| Repository | Description | Stars | 
|---|---|---|
|  | A repository of public datasets for building recommender systems. | 993 | 
|  | A library providing a comprehensive set of metrics and tools for evaluating recommender systems | 278 | 
|  | A library for building and using collaborative filtering-based recommender systems | 1,477 | 
|  | A collection of real-world datasets and practical reinforcement learning baselines for recommendation systems. | 220 | 
|  | A Django-based website demonstrating how to implement recommender algorithms with a dataset from themoviedb.org API. | 909 | 
|  | A library providing evaluation metrics and diagnostic tools for recommender systems. | 571 | 
|  | A framework for building and deploying scalable recommendation algorithms | 1,814 | 
|  | A comprehensive and efficient recommendation system library with Python and PyTorch support | 3,497 | 
|  | Provides tools and models for building and comparing meta learning recommendation systems in Python. | 23 | 
|  | Provides algorithms and utilities for candidate recommendations in RDF data | 3 | 
|  | A comprehensive library of algorithms and techniques for building recommender systems | 1,102 | 
|  | Enables reproducible data processing and sharing through standardization and packaging | 154 | 
|  | A recommender system built using multiple candidate selection and ranking methods for predicting next item likes in a streaming data environment. | 54 | 
|  | An academic project providing a framework for building and evaluating recommender systems in MATLAB. | 47 | 
|  | A simple recommendation system built on top of Go, allowing users to create tables with user ratings and retrieve personalized recommendations. | 314 |