pymc-devs / pymc-resources

PyMC educational resources
MIT License
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bayesian-inference bayesian-statistics data-analysis data-science

PyMC3 Resources

PyMC3 educational resources, including the PyMC3 port of the following books (original models in STAN/BUGS/JAGS etc,.):

How to contribute

Thanks wanting to contribute! These resources are a community effort and we, and all future resource users, appreciate your help.

If just starting

  1. Reading the contributing guide for pymc is a good place to start. The guide will familiarize you with the high level tools and workflow.
    • Some of the instructions will differ so read the below steps first.
  2. In this repo the environments are defined per resource. Look into each directory to find the environment file and use that
  3. When ready to contribute open a draft PR stating the scope of work as early as possible. This helps avoid duplicate work early.
  4. If you have further questions don't hesitate to ask on https://discourse.pymc.io/.

License

Unless otherwise stated in the directory containing the codes, all codes are copyrighted by their author(s) under MIT license.