1Cademy - Explanations from The Book of Why about Bayesian Networks

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Explanations from "The Book of Why" about Bayesian Networks

before discussing Bayesian networks, Pearl discusses the history and significance, using examples to further explain the concepts, of Bayes' rule and inverse probability from pages 95 - 108
Pearl then connected this concept to Bayesian networks by discussing belief propagation from pages 108 - 112
references past sections: "Although Bayes didn't know it, his rule for inverse probability represents the simplest Bayesian network. We have seen this network in several guises now: Tea -> Scones, Disease -> Test, or, more generally, Hypothesis -> Evidence" (Pearl, 2018, p. 112)
explains the junctions present in both Bayesian networks and causal diagrams, using examples, from pages 113-116
from pages 117 - 122, Pearl discusses conditional probability tables in relation to Bayesian networks and also mentions inverse-probability (previously discussed starting pages 97-99)
from pages 122 - 133, Pearl discusses Bayesian networks in various contexts
for the rest of the chapter (pages 128 - 133), Pearl compares Bayesian networks and causal diagrams

Updated 2020-05-11

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