Advance Bayesian Modelling with PyMC3


#1

Dear all,

Last month I did a 2 days workshop in the Czech Republic (hosted by CEAi). They prepared professional video recording, which I would like to share here. This is a high-level PyMC3 workshop, as the attendees had already work through Introduction to Probabilistic programming (with PyMC3), which is built on top of the tutorials by @fonnesbeck. But the workshop also covers all the basics in depth. Due to the time limit, I did not manage to present more case studies - it would definitely be something to improve upon for next time :slight_smile:

The code and slide could be found below:

Video content

Session 1: Probabilistic thinking: generative model and likelihood computation
Session 2: Likelihood in PyMC3 and model reparameterization
Session 3: Model parameterization and coordinate system: Neal’s funnel
Session 4: Bayesian modelling and inference with MCMC in PyMC3
Session 5: Model evaluation and model comparison
Session 6: Case study: modelling multivariate observation
Session 7: Mixing MCMC samplers: Compound step in PyMC3


Fitting multiple measurements, shape issues in sample_ppc
#2

This is awesome, Thank you Junpenglao!


#3

This is very rich. Thank you for sharing.


#4

This is awesome! Thank you for sharing!


#5

Wow, this is phenomenal. Way to kill my weekend ^______^.


#6

thank you sir!


#7

Wow, amazing stuff, @junpenglao! Thank you for sharing with us :slight_smile:


#8

This is so good, well done!


#9

Lots of content. Thank you!