When Can You Actually Trust a Machine Learning Model?
python
dev.to
Building a machine learning model is relatively straightforward today. You train it. Evaluate it. Tune it. Eventually, you get a model that performs well. But a more difficult question comes after: Can you trust it? Not occasionally. Not in controlled environments. But consistently in the real world. The Illusion of Trust Many people assume trust comes from metrics. If a model has: Accuracy: 94% It feels reliable. But accuracy doesn’t tell you: when the model will fail how it wil