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A 2day course covering Bayesian modelling with Stan, a principled workflow and some more advanced tips and tricks

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Prob. Prog. Training

Repository for the Probabilistic Programming Course

30-31 July 2020

 DataJavelin Ltd, Dr Peter Hurley

Files

  • Thursday/: folder with notebooks
  • assets/: folder containing images used in notebooks
  • orig_golf_data.txt golf data for part II and III
  • Dockerfile: Dockerfile for building docker container

Requirements for Course

A laptop with working Python 3 installation with PyStan and Jupyter notebook installed would be useful.

Alternatively, participants can use our docker image, which has fully working software stack (including Jupyter notebook). Can be found on our docker hub repository https://hub.docker.com/r/datajavelin/discnet:0.2 and would suggest downloading before course.

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A 2day course covering Bayesian modelling with Stan, a principled workflow and some more advanced tips and tricks

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