In what ways can automated testing be applied to ML models in an MLOps pipeline?

Instruction: Explain how automated testing can be integrated into MLOps pipelines to ensure the reliability and quality of machine learning models.

Context: This question assesses the candidate's knowledge of applying software engineering best practices, like automated testing, to machine learning workflows, ensuring models are robust and reliable before and after deployment.

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The way I'd think about it is this: Automated testing in MLOps goes beyond unit tests. I want data-schema tests, feature validation, training-pipeline tests, inference API tests, regression tests on known cases, and where possible checks on...

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