Data Science Statistics
Bayesian networks are graphical models that represent a set of variables and their conditional dependencies through directed acyclic graphs (DAGs). These networks allow for the modeling of complex relationships between variables using Bayes' theorem, enabling inference and decision-making under uncertainty. They connect to the foundational principles of Bayesian probability and inference, making them a powerful tool for reasoning about uncertain information and updating beliefs based on new evidence.
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