Machine Learning at the Wikimedia Foundation
Welcome to the homepage of the Wikimedia Foundation's Machine Learning team.
- Design, build, and maintain the foundation's machine learning infrastructure.
- Plan, train, deploy, and manage production machine learning models created or requested by Wikimedia teams or Wiki communities.
- Develop best practices for applied ethical machine learning.
Working with us
Have a question? Want to talk to the team or our community of volunteers about machine learning? Here are the best ways to connect with us.
Discuss machine learning and watch the team work joining our public IRC chatroom
Have a longer question? Want to follow what the team is working on? Visit our live blog. Visit our talk page
- Lift Wing -- A scalable machine learning model serving infrastructure build off Kubeflow.
- ORES -- Machine learning prediction as a web service (see the list of tools that use ORES)
- m:Wiki labels -- Training interface where Wikipedians teach machines how to perform important tasks
- revscoring -- A machine prediction "scoring" framework for building prediction models used by ORES
- JADE [Archived] -- Robust false-positive and feedback gathering system, to allow human refutation and review of ORES scoring.
Former staff and volunteers
- とある白い猫 (IEG)
- Arthur Tilley (IEG)
- He7d3r (IEG/Volunteer)
- YuviPanda (Volunteer)
- Sumit (Research Intern)
- Ewitch (Research Intern)
- Marius Hoch (Software Engineer)
- Max Klein (Software Engineer)
- Adam Wight (Software Engineer)
- Natalia Timakova (Research Intern)
- Amir Sarabadani (Software Engineer)
- Nate TeBlunthuis (Research Intern)
- James Hare (Associate Product Manager)
- Aaron Halfaker (Principal Research Scientist & Team Lead)
- Habeeb Shopeju (Software Engineering Intern)