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Probabilistic Graphical Models (PGMs)
Probabilistic Graphical Models are a way to represent complex relationships between many variables using a graph structure, where nodes are variables and edges indicate dependencies. They combine probability theory and graph theory to allow reasoning under uncertainty. These models can explicitly show how one variable's state affects the likelihood of another's.
In plain terms
PGMs are like a detailed flowchart that not only shows steps but also the probability of success or failure at each decision point.
Why it matters
They are crucial for tasks like medical diagnosis, speech recognition, and understanding causal relationships where uncertainty is inherent and needs to be formally managed.
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