Markov Chain Monte Carlo

author: Iain Murray, School of Informatics, University of Edinburgh
published: Nov. 2, 2009,   recorded: August 2009,   views: 236193


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Download slides icon Download slides: mlss09uk_murray_mcmc.pdf (1.7┬áMB)

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Reviews and comments:

Comment1 Kathryn, January 18, 2010 at 12:12 a.m.:

Awesome, thanks to the lecturer and whoever taped it!

Comment2 zsjyhh, November 24, 2010 at 9 a.m.:

Very good!!!

Comment3 ben, November 29, 2010 at 12:02 p.m.:

It is practically impossible to follow since the video is usually not of the whiteboard, but of the lecturer.

Comment4 Nathaniel, April 11, 2011 at 9:31 p.m.:

Very good lecture.

The presenter is clear, organized, and presents some interesting material that is often not found in textbooks.

Comment5 Iain Murray, December 17, 2011 at 3:06 p.m.:

Viewers of this video may want to try the practical exercise that I provided at this summer school. It's available at

Comment6 Timmy, February 27, 2012 at 2:02 a.m.:

One of the best MCMC tutorials I watched..

Comment7 S, March 26, 2012 at 10:12 a.m.:

This is so great, thank you very much!

Comment8 bg284, April 5, 2012 at 11:12 p.m.:

thanks so much for this tutorial. really demystified MCMC for me, and for the short note you pasted on your website as well.

Comment9 Sandip, May 24, 2012 at 9:43 p.m.:

Is it possible to download this video?

Comment10 Sam, June 29, 2012 at 2:08 p.m.:

Extremely clear tutorial, thanks very much for putting this online Iain.

Comment11 Conor, March 15, 2013 at 8:56 a.m.:

Sandip has already asked- but can I download this video from anywhere? I'm trying to watch it in Malawi... the internet speeds are not the best! (Sandip- it is on YouTube too)

Comment12 Iain Murray, March 18, 2013 at 12:17 p.m.:

Conor: now that the videos are on YouTube, there's lots of ways to download them for personal use. For example the python script and many others. You'll want the pdf of the slides from to go with the video.

Comment13 Andrii Cherniak, December 27, 2013 at 10:52 p.m.:

This is definitely a much better explanation than in Nando de Freitas class. Not that i am saying that Nando does not explain - he does. But this lecture provides a more coherent path in my opinion

Comment14 Yaser, April 17, 2014 at 5:11 a.m.:

It was a really good intro lecture on MCMC inference.
I'm wondering if someone tried to explain some more advanced features on it like the forward-backward recursion in MCMC inference.
Also, I think providing an actual example of usage of this method on a Bayesian net would also made it more than perfect.

Comment15 sam, January 17, 2016 at 6:44 a.m.:

amazing. clear. explain that you want to hear instead of textbook definitions.

Comment16 Chris, January 22, 2016 at 7:59 a.m.:

I feel sad because my English listening ability is not good enough to let me understand what the lecturer is talking about,although I actually know it is a good presentation !

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Comment19 David Ing, February 8, 2021 at 4:15 p.m.:

This is a piece of a very good topic.

Comment20 Micah, February 8, 2021 at 4:18 p.m.:

This is a good lecture. Thank you!

Comment21 Ken Hobbs, February 8, 2021 at 4:19 p.m.:

Thank you so much. I learned something today.

Comment22 Sunny, September 11, 2021 at 9:39 a.m.:

This is a great article. Thanks.

Comment23 Annalisa, September 24, 2021 at 5:56 a.m.:

A very well said. thanks for the tutorial.

Comment24 Gian, October 25, 2021 at 6:36 p.m.:

Thanks for keeping us here updated.

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Comment26 Pink, December 30, 2021 at 2:44 p.m.:

Thank you for sharing your learnings. I appreciate it so much!

- Pink |

Comment27 Liam, December 31, 2021 at 6:33 a.m.:

Thank you for sharing this. I've learned a lot just by listening to this discussion.

Comment28 John, December 31, 2021 at 3:54 p.m.:

The way you discuss it makes it easier for us to understand this Markov Chain. Thank you for sharing this.

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