Examples and notebooks of using PyMC3 for learning Bayesian Analysis
Repo for Tutorial on Getting started with Bayesian Analysis and PyMC3.
In case you wish to have a look, the slides are at: https://speakerdeck.com/ramnarasimhan/getting-started-with-bayesian-analysis-and-pymc3
In the notebooks/ folder, there are 3 notebooks with Examples:
Example1_Linear_Regression_Using PyMC3.ipynb
Example2_OilExporation_Success_probability_using_PyMC3.ipynb
Example3_AB Testing in a Bayesian Framework Using PyMC3.ipynb
For some participants, it might be easier to follow these notebooks along with the Slides in the presentation.
You really only need PyMC3
- To install PyMC3 use
pip install pyMC3 - To install arviz try
pip install arviz
> conda create -n bayes python=3.8
> conda activate bayes
pip install -r requirements.txt
To make your virtual env show up in Jupyter you have to type:
python -m ipykernel install --user --name=bayes
If you get an error about ipykernel, install it using: conda install -c anaconda ipykernel