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Artificial intelligenceDefine prior probability and conditional probability. State Bayes's theorem. How is it useful for decision making under uncertainty.20227mArtificial intelligenceCompare probabilistic reasoning using Bayesian Networks with logical reasoning. In what situations is probabilistic reasoning more appropriate? Give examples.20247mArtificial intelligenceBayesian networks are especially useful in situations with: (i) Complete knowledge and logic (ii) No uncertainty (iii) Deterministic processes (iv) Probabilistic and uncertain information20242mArtificial intelligenceBayesian Networks are used to handle (i) Certain knowledge (ii) Uncertain knowledge (iii) Deterministic knowledge (iv) Syntax only20252m
PreviousWhat makes the difference between good decisions and bad decisions? (i) A good decision is based on logic (ii) A good decision considers all available data (iii) A good decision considers all alternatives (iv) A good decision applies quantitative approachesNextWhich of the following steps/assumptions in regression modeling impacts the trade-off between under-fitting and over-fitting the most? (i) The polynomial degree (ii) Whether we learn the weights by matrix inversion or gradient descent (iii) The use of a constant-term (iv) None of the above