7 Recommender System Frameworks for Efficient and Scalable Recommendation Algorithms

Open Source RecSys Frameworks

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  EasyRec

  

  EasyRec is a framework for large scale recommendation algorithms.

  License: Apache License 2.0

  GitHub
  
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  Gorse

  

  Gorse aims to be a universal open-source recommender system that can be quickly introduced into a wide variety of online services.

  License: Apache License 2.0

  GitHub
  Website: https://gorse.io
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  Implicit

  

  Implicit provides fast Python implementations of several different popular recommendation algorithms for implicit feedback datasets

  License: MIT License

  GitHub
  Website: https://benfred.github.io/implicit/
• 

  LightFM

  

  LightFM is a Python implementation of a number of popular recommendation algorithms for both implicit and explicit feedback

  License: Apache License 2.0

  GitHub
  
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  NVTabular

  

  NVTabular is a feature engineering and preprocessing library for tabular data that is designed to easily manipulate terabyte scale datasets and train deep learning (DL) based recommender systems.

  License: Apache License 2.0

  GitHub
  
• 

  Merlin

  

  NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in production.

  License: Apache License 2.0

  GitHub
  
• 

  Surprise

  

  Surprise is a Python scikit for building and analyzing recommender systems that deal with explicit rating data.

  License: BSD 3-Clause "New" or "Revised" License

  GitHub
  Website: http://surpriselib.com

Last Updated: Dec 26, 2023