A Data-Centric Optimization Framework for Machine Learning

DaCeML is a Data-Centric Machine Learning framework that provides a simple, flexible, and customizable pipeline for optimizing training of arbitrary deep neural networks.

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Cite this as

Tal Ben-Nun, Oliver Rausch, Nikoli Dryden (2024). Dataset: A Data-Centric Optimization Framework for Machine Learning. https://doi.org/10.57702/74ecfvul

DOI retrieved: December 16, 2024

Additional Info

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Created December 16, 2024
Last update December 16, 2024
Author Tal Ben-Nun
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Oliver Rausch
Nikoli Dryden
Homepage https://github.com/spcl/daceml