Discussion on statistical foundations of a Bayesian spam-detection model already in production.

Compare prior, likelihood and posterior for a Beta-Binomial click-through model. Derive how the posterior mean acts as a smoothed estimate; when is it preferred to MLE? Explain how Bayesian credible intervals differ from frequentist confidence intervals in the context of model calibration. You observe concept drift; how would you update the prior or hierarchy to adapt more quickly?

Use equations, reference conjugacy, and tie answers back to practical model monitoring.

Snapchat Data Scientist interview question: How to Update Bayesian Model for Concept Drift?. {"blocks": [{"key": "ee7ccbfa", "text": "Scenario", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {...