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Bayesian Machine Learning
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35:55
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UofU Data Science
Machine learning: Lecture 23b: Bayesian learning
In this lecture, we will look at probabilistic criteria for defining what it means to learn. Specifically, we will see maximum a posteriori and maximum likelihood learning criteria with examples. For more details visit https://svivek.com/teaching/machine-learning/spring2023/lectures/prob-learning.html
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