ML Testing - HelpMeTest

ML Testing

AI Bias Testing: How to Detect and Measure Fairness Issues in ML Models

ML models trained on historical data inherit historical biases. A hiring model trained on past decisions might discriminate by gender. A credit scoring model might perpetuate racial bias from historical lending practices. A medical risk model might underperform for underrepresented demographic groups. Testing for bias isn't optional — it&

AI Testing

How to Test Computer Vision Models: PyTorch, OpenCV, and YOLO

Computer vision models break in ways that unit tests don't catch. Your preprocessing pipeline silently changes a pixel value range, your bounding box coordinates are in the wrong format, or your model returns detections in a different order than your downstream code expects. None of these show up

Machine Learning

ML Model Validation: Train/Test Split, Cross-Validation, and Holdout Sets

A machine learning model that performs well on training data is meaningless. What matters is whether it generalizes to data it hasn't seen. Model validation is the discipline of measuring that generalization — reliably, without cheating. This guide covers the core validation techniques, when to use each, and the