george0st/qgate-model
A meta-model framework for independent testing and quality assurance of machine learning solutions using synthetic datasets.
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This project provides a machine learning meta-model that generates synthetic data for benchmarking and testing ML pipelines. It defines ML artifacts including projects, feature sets, feature vectors, pipelines, and models in a solution-agnostic format. The framework enables comparison of ML platform capabilities and regression testing across versions of MLRun/Iguazio/Nuclio deployments through unit, integration, and acceptance tests.
Frequently asked
- What is george0st/qgate-model?
- A meta-model framework for independent testing and quality assurance of machine learning solutions using synthetic datasets.
- Is qgate-model open source?
- Yes — george0st/qgate-model is open source, released under the Apache-2.0 license.
- What language is qgate-model written in?
- george0st/qgate-model is primarily written in Python.
- How popular is qgate-model?
- george0st/qgate-model has 411 stars on GitHub.
- Where can I find qgate-model?
- george0st/qgate-model is on GitHub at https://github.com/george0st/qgate-model.