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Machine learning: Lecture 23b: Bayesian learning

YouTubeUofU 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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