4 Ways to Test ML Models in Production

Testing machine learning models in production is crucial for reliability. Four key strategies are A/B testing, canary testing, interleaved testing, and shadow testing. These methods allow models to be tested on real-world data while minimizing risk and user impact. Tools like Maxim can aid in simulating, evaluating, and observing AI agents for better performance before deployment.