How do you design and analyze A/B tests for ML models? What statistical considerations are important, and how do you avoid common pitfalls?

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A/B testing compares ML model variants by randomly assigning users to control and treatment groups and measuring differences in business metrics. Unlike offline evaluation, A/B tests capture real user behavior and downstream business impact, making them the gold standard for…