ML Testing

Test ML models, data pipelines, and features comprehensively. Covers ML testing pyramid (data, feature, model, integration, system tests), model unit tests (prediction shape, output range, determinism), quality gate tests (accuracy thresholds, performance benchmarks), behavioral testing (invariance, directional, minimum functionality), metamorphic testing, regression testing, smoke tests, shadow testing, A/B testing, load testing, data pipeline testing, property-based testing with Hypothesis, pytest fixtures, synthetic data generation, CI/CD integration, and test coverage for ML code. Use when writing tests for ML systems or setting up quality gates.