This comprehensive lesson teaches how to test ML artifacts including code, data, and models to build a reliable ML system. It covers the intuition behind testing, different types of tests (unit, integration, system, acceptance, regression), best practices, and implementation details for testing code, data expectations, and model behavior.
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