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Valor is a centralized evaluation store which makes it easy to measure, explore, and rank model performance.

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Valor: A Centralized Evaluation Store

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Valor is a centralized evaluation store which makes it easy to measure, explore, and rank model performance. Valor empowers data scientists and engineers to evaluate the performance of their machine learning pipelines and use those evaluations to make better modeling decisions in the future.

Valor is maintained by Striveworks, a cutting-edge MLOps company based out of Austin, Texas. It's core developers are Charles Zaloom, Nick Lind, Benjamin Nativi, and Eric Korman.

We'd love to learn more about your interest in Valor and answer any questions you may have; please don't hesitate to reach out to us on Slack or GitHub.

For more information, please see our user docs.