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All code for this workshop is available on GitHub. We encourage you to play around with the examples as you follow along. Bayesian inference gives us a recipe for optimally revising uncertain beliefs after receiving evidence. Often times, we have good models of how hidden states of the world produce different outcomes, but we want to know what those hidden states are. Bayes’ rule gives us a recipe for solving such inverse problems.