Machine Learning: Tests and Production
Best practices for testing ML-based systems.
unit-tests e2e-tests production systems-design tests testing checklist tutorial article

“Creating reliable, production-level machine learning systems brings on a host of concerns not found in small toy examples or even large offline research experiments. Testing and monitoring are key considerations for ensuring the production-readiness of an ML system, and for reducing technical debt of ML systems.” - The ML Test Score: A Rubric for ML Production Readiness and Technical Debt Reduction

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