# Bayesian Linear Regression and Maximum Likelihood Estimates

## Метаданные

- **Канал:** Steve Brunton
- **YouTube:** https://www.youtube.com/watch?v=qTRgdhgmFyc
- **Дата:** 21.04.2026
- **Длительность:** 19:15
- **Просмотры:** 11,362

## Описание

In this video we show that the least squares regression fit is the maximum likelihood estimate assuming Gaussian noise on the measurements.  This is a powerful fact that will allow us to incorporate prior information in the Bayesian framework. 

This video was produced at the University of Washington, and we acknowledge funding support from the Boeing Company

## Содержание

### [0:00](https://www.youtube.com/watch?v=qTRgdhgmFyc) Segment 1 (00:00 - 05:00)

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### [5:00](https://www.youtube.com/watch?v=qTRgdhgmFyc&t=300s) Segment 2 (05:00 - 10:00)

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### [10:00](https://www.youtube.com/watch?v=qTRgdhgmFyc&t=600s) Segment 3 (10:00 - 15:00)

ass e for e for of e for

### [15:00](https://www.youtube.com/watch?v=qTRgdhgmFyc&t=900s) Segment 4 (15:00 - 19:00)

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*Источник: https://ekstraktznaniy.ru/video/52885*