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@miguelgfierro @datashinobi @gramhagen @motefly @anargyri
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Contributors to Recommenders

Recommenders is developed and maintained by a community of people interested in exploring recommendation algorithms and how best to deploy them in industry settings. The goal is to accelerate the workflow of any individual or organization working on recommender systems. Everyone is encouraged to contribute at any level to add and improve the implemented algorithms, notebooks and utilities.

Maintainers (sorted alphabetically)

Maintainers are actively supporting the project and have made substantial contributions to the repository.
They have admin access to the repo and provide support reviewing issues and pull requests.

  • Andreas Argyriou
    • SAR single node improvements
    • Reco utils metrics computations
    • Tests for Surprise
  • Jeremy Reynolds
    • Reference architecture
  • Jun Ki Min
    • ALS notebook
    • Wide & Deep algorithm
  • Le Zhang
    • Reco utils
    • Continuous integration build / test setup
    • Quickstart, deep dive, algorithm comparison, notebooks
  • Miguel González-Fierro
    • Recommendation algorithms review, development and optimization.
    • Reco utils review, development and optimization.
    • Github statistics.
    • Continuous integration build / test setup.
  • Nikhil Joglekar
    • Improving documentation
    • Quick start notebook
    • Operationalization notebook
  • Scott Graham
    • Improving documentation
    • VW notebook
  • Tao Wu
    • Improving documentation

Contributors (sorted alphabetically)

Full List of Contributors

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