8000 GitHub - seabbs/prob-epi: Course materials of "Bayesian Modelling and Probabilistic Programming" with NumPyro, initially created for "AI for Science" MSc at African Institute for Mathematical Sciences (AIMS)
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Course materials of "Bayesian Modelling and Probabilistic Programming" with NumPyro, initially created for "AI for Science" MSc at African Institute for Mathematical Sciences (AIMS)

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https://elizavetasemenova.github.io/prob-epi

Giving feedback

  • To correct typos, please make pull requests on GitHub. If these notes ever get published, I will list your name in Acknowledgements.

  • For more substantial suggestions about the course content, such as desired topics, please use issues on GitHub or email them to elizaveta [dot] p [dot] [insert my surname] [at] gmail [dot] com.

  • If you enjoyed the content and / or learnt from it, please leave a 'star' to the book's GitHub repository.

  • If you are creating a written document (a paper, report, book chapter) where you use what you've learnt here, please cite

@book{semenova24,
  author = {Semenova, Elizaveta},
  title = {Bayesian Modelling and Probabilistic Programming with Numpyro and examples from Epidemiology.},
  year = {2024},
  source = {https://elizavetasemenova.github.io/prob-epi},
  doi = {https://doi.org/10.5281/zenodo.11550659}
}

Conda environment

To run the code examples from the course, the recommended Conda environemnt can be created as follows:

conda create -n aims python=3.9
conda activate aims
conda install -c conda-forge jupyter-book
conda install conda-forge::matplotlib
conda install numpy
conda install conda-forge::ghp-import
conda install conda-forge::numpyro
conda install conda-forge::jax
pip install sphinxcontrib-tikz
conda install conda-forge::geopandas
conda install conda-forge::arviz
conda install anaconda::seaborn
pip install pyppeteer

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Course materials of "Bayesian Modelling and Probabilistic Programming" with NumPyro, initially created for "AI for Science" MSc at African Institute for Mathematical Sciences (AIMS)

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