This lecture covers the theory behind Gaussian processes, the MAP rule, sufficiency, irrelevance, and the design of receivers using MAP calculations and maximum likelihood estimation.
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Explores linear regression from a statistical inference perspective, covering probabilistic models, ground truth, labels, and maximum likelihood estimators.
