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Great video. I've been impressed with the number of variables PyMC3 can handle (I've created models with 2,000+). Theano compilation time can get very long, though, requiring more time than the actual sampling at times.
Allen Downey recommends a half-Cauchy for Nu, and sigma... maybe, i am misunderstanding something though.
Is there any github link to point out to the presentation?
Thanks for the video. I had to stop listening and look at the slides though because of how often you said 'Uh' and 'Um'. Something to work on :)
The 'aaa's are very distracting.
Great video. I've been impressed with the number of variables PyMC3 can handle (I've created models with 2,000+). Theano compilation time can get very long, though, requiring more time than the actual sampling at times.
Allen Downey recommends a half-Cauchy for Nu, and sigma... maybe, i am misunderstanding something though.
Is there any github link to point out to the presentation?
Thanks for the video. I had to stop listening and look at the slides though because of how often you said 'Uh' and 'Um'. Something to work on :)
The 'aaa's are very distracting.