How Probabilistic Graphical Models Represent Uncertainty
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Probability can become hard to reason about when many variables interact. One variable affects another. Evidence changes belief. Dependencies start to form a network. That is where Probabilistic Graphical Models become useful. Core Idea A Probabilistic Graphical Model represents uncertainty with a graph. The nodes are random variables. The edges represent relationships between them. Instead of treating probability as a flat list of formulas, a PGM gives it structure. That structure makes complex