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A Robust Schema for Storing and Managing Machine Learning Data and Models- Machine Learning (ML) has enabled models that can improve efficiency and decrease computational cost
- ML models are crucial in enabling Integrated Computational Materials Engineering (ICME)
- Large data sets require robust means of storing ML data and models
Document ID
20230001128
Acquisition Source
Glenn Research Center
Document Type
Presentation
Authors
Brandon L. Hearley
(Glenn Research Center)
Steven M. Arnold
(Glenn Research Center Cleveland, Ohio, United States)
Joshua Stuckner
(Glenn Research Center Cleveland, Ohio, United States)
Date Acquired
January 24, 2023
Subject Category
Cybernetics, Artificial Intelligence and Robotics
Meeting Information
Meeting: AIAA Science and Technology (SciTech) Forum and Exposition 2023
Location: National Harbor, MD
Country: US
Start Date: January 23, 2023
End Date: January 27, 2023
Sponsors: American Institute of Aeronautics and Astronautics
Funding Number(s)
WBS: 109492
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
Technical Review
NASA Peer Committee
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