Probabilistic models are mathematical frameworks that use probability distributions to represent uncertain outcomes and the relationships between variables. They are essential in capturing the inherent uncertainty in data and can be employed to make predictions, infer conclusions, and guide decision-making processes in various fields such as machine learning and AI. These models leverage statistical techniques to analyze and interpret complex data sets, enabling more informed decisions based on likelihoods rather than certainties.
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