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Bayesian ML really shines in hierarchical models , one thing that quickly comes to mind is the walmart dataset in kaggle ,may be you can use bayesian ml to model the probability distribution of demand of a product of a store , where store’s parameter comes from a global distribution of different stores across the dataset
Maybe healthcare or medical diagnosis use cases
Naive bayes is also pretty good with document classification or sentiment analysis. If subject/industry isn’t a a concern, there’s plenty of fun datasets on kaggle.
Naive bayes is not a necessarily a bayesian model .In most cases ( and in most implementations of it ) You are using “frequentist “ version of it and estimating parameters using a maximum likelihood estimate , even though it has a prior and posterior ,the prior is not a bayesian prior