Bayesian Linear Regression and Maximum a Posteriori (MAP) Estimate
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Bayesian Linear Regression and Maximum a Posteriori (MAP) Estimate

Steve Brunton 24.04.2026 6 410 просмотров 183 лайков

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In this video we show how to incorporate prior information into the least squares regression, consistent with the framework of Bayesian statistics. The so-called maximum a posteriori (MAP) estimate is one of the foundational tools in statistical fitting and machine learning. This video was produced at the University of Washington, and we acknowledge funding support from the Boeing Company

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Другие видео автора — Steve Brunton

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