Dr Peter Hurley and Dr Philip Rooney
- DISCNet_Course.ipynb: Notebook for first part of course
- DISCNet_Course_PartII.ipynb: Notebook for second part of course
- assets/: folder containing images used in notebooks
- co2_annmean_mlo.txt: Carbon dioxide data file used in course
- Dockerfile: Dockerfile for buidling docker container
- FACYNation_BDT.ipynb: Notebook for Bayesian Decision Theory (BDT) example
- FACYnation_crop_yield.stan: Stan model used by BDT example
- eastbourne.txt: Weather data used in BDT example
A laptop with working Python 3 installation with PyStan and Jupyter notebook installed would be useful.
Alternatively, students 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 and would suggest downloading before course.