Bayesian Models

Bayesian models are statistical models that use Bayes' theorem to update probabilities as new data becomes available. In Bayesian modeling, prior knowledge or beliefs about the data are combined with the likelihood of the data to produce a posterior distribution of the parameters of interest. Bayesian models are particularly useful in situations where the sample size is small or the data is noisy, as they allow for the incorporation of prior knowledge to improve the accuracy of the estimates. Bayesian models are widely used in machine learning, data science, and artificial intelligence applications, including natural language processing, computer vision, and recommendation systems.
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