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

3m read timeFrom blog.dailydoseofds.com
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4 Ways to Test ML Models in Production#1) A/B testing#2) Canary testing#3) Interleaved testing#4) Shadow testing
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