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We're glad you're here. It means you're ready to leverage TruEra's AI Quality Platform to analyze and improve your AI/ML modeling projects. In this repository, you'll find sample projects of integrating machine learning models with TruEra to help you get the most out of the TruEra Python SDK.
Why TruEra?
As you build and deploy ML models, TruEra plugs into your ML stack to let you test, debug and monitor your projects to ensure each model is doing what it's supposed to be doing — and, if not, why not? From feature development that helps you refine your data to efficiently training and evaluating your models to validating a final model for production, TruEra has you covered.
Which examples should I use?
To learn how to create and ingest your first project in TruEra, use the SDK Quickstart. If you'd rather explore a particular AI Quality concept such as performance, drift or fairness - start with a "Starter Example". These notebooks, each in two parts, will walk you through testing your ML model for a particular issue and how to improve your model along that axis. Last, if there's a particular framework or environment you'd like to integrate with - check out the Integrations & Extensions section!