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This hands-on tutorial introduces practical Bayesian inference using PyMC, focusing on A/B testing, decision-making under uncertainty, and hierarchical modeling. With real-world examples, you'll learn how to build and interpret Bayesian models, evaluate competing hypotheses, and implement adaptive strategies like Thompson sampling. Whether you ...
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