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NitroML is a modular, portable, and scalable model-quality benchmarking framework for Machine Learning and Automated Machine Learning (AutoML) pipelines.

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NitroML

NitroML is a framework for benchmarking Automated Machine Learning (AutoML) pipeline model-quality.

Our mission is to provide model-quality benchmarking tools to accelerate AutoML research and development.

More generally, NitroML enables AutoML research teams to iterate more quickly on their highly-customized, heterogeneous, and multi-stage pipelines. It offers machine learning model-quality benchmarking best practices out-of-the-box, curates raw datasets, and leverages [TFX:OSS] to scale with Cloud-resources. Its benchmark database and analysis tools ensure that AutoML teams can be data-driven as they modify their systems.

This is not an officially supported Google product.

For more information, see go/nitroml.

Open Source Agenda is not affiliated with "Nitroml" Project. README Source: google/nitroml
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