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https://github.com/google/nitroml

NitroML is a modular, portable, and scalable model-quality benchmarking framework for Machine Learning and Automated Machine Learning (AutoML) pipelines.
https://github.com/google/nitroml

automl benchmarking kubeflow machine-learning model-quality modular portable python scale tfx

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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.