Markov Chain Monte Carlo
author: Iain Murray,
School of Informatics, University of Edinburgh
published: Nov. 2, 2009, recorded: August 2009, views: 236144
published: Nov. 2, 2009, recorded: August 2009, views: 236144
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Reviews and comments:
Awesome, thanks to the lecturer and whoever taped it!
Very good!!!
It is practically impossible to follow since the video is usually not of the whiteboard, but of the lecturer.
Very good lecture.
The presenter is clear, organized, and presents some interesting material that is often not found in textbooks.
Viewers of this video may want to try the practical exercise that I provided at this summer school. It's available at http://homepages.inf.ed.ac.uk/imurray...
One of the best MCMC tutorials I watched..
This is so great, thank you very much!
thanks so much for this tutorial. really demystified MCMC for me, and for the short note you pasted on your website as well.
Is it possible to download this video?
Extremely clear tutorial, thanks very much for putting this online Iain.
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)
Conor: now that the videos are on YouTube, there's lots of ways to download them for personal use. For example the python script http://rg3.github.com/youtube-dl/ and many others. You'll want the pdf of the slides from videolectures.net to go with the video.
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
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.
amazing. clear. explain that you want to hear instead of textbook definitions.
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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Markov Chain Monte Carlo (MCMC) is a statistical technique for approximating the posterior distribution of a model. MCMC can be used to estimate parameters in a Bayesian model, or to generate samples from a complex probability distribution. That's all I know.
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