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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.
Is there any github link to point out to the presentation?
Allen Downey recommends a half-Cauchy for Nu, and sigma... maybe, i am misunderstanding something though.
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.
Is there any github link to point out to the presentation?
Allen Downey recommends a half-Cauchy for Nu, and sigma... maybe, i am misunderstanding something though.
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.