FAIRness Along the Machine Learning Lifecycle Using Dataverse in Combination with MLflow
Typical Machine Learning (ML) approaches are characterized by their iterative and exploratory nature: continuously refining and adapting not only code but also ML models to optimize the results and the performance on new data. This poses novel challenges related to keeping the trained model Findable...
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Main Authors: | Lincoln Sherpa, Valentin Khaydarov, Ralph Müller-Pfefferkorn |
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Format: | Article |
Language: | English |
Published: |
Ubiquity Press
2024-12-01
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Series: | Data Science Journal |
Subjects: | |
Online Access: | https://account.datascience.codata.org/index.php/up-j-dsj/article/view/1731 |
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