How to do Bayesian statistical modelling using numpy and PyMC3

To get started, first identify whether you

1. Prefer to use the conda package manager (which ships with the Anaconda distribution of Python), or if you
2. prefer to use pipenv, which is a package authored by Kenneth Reitz for package management with pip and virtualenv, or if you
3. Do not want to mess around with dev-ops.

If this is the first time you're setting up your compute environment, use the conda package manager to install all the necessary packages from the provided environment.yml file.

conda env create -f environment.yml

To activate the environment, use the conda activate command.

conda activate bayesian-stats-modelling

If you get an error activating the environment, use the older source activate command.

source activate bayesian-stats-modelling

To update the environment based on the environment.yml specification file, use the conda update command.

conda env update -f environment.yml

Instructions are coming.

If you don't want to mess around with dev-ops, click the following badge to get a Binder session on which you can compute and write code.

• Baseball dataset