We recently released PyMC3 3.1 after the first stable 3.0 release in January 2017. You can update either via pip install pymc3 or via conda install -c conda-forge pymc3 .

A lot is happening in PyMC3-land. One thing I am particularily proud of is the developer community we have built. We now have around 10 active core contributors from the US, Germany, Russia, Japan and Switzerland. Specifically, since 3.0, Adrian Seyboldt, Junpeng Lao and Hannes Bathke have joined the team. Moreover, we have 3 Google Summer of Code students: Maxime Kochurov, who is working on Variational Inference; Bill Engels, who is working on Gaussian Processes, and Bhargav Srinivasa is implementing Riemannian HMC.

Moreover, PyMC3 is being seeing increased adoption in academia, as well as in industry.

Here, I want to highlight some of the new features of PyMC3 3.1.

Discourse forum + better docs¶

To facilitate the community building process and give users a place to ask questions we have a launched a discourse forum: http://discourse.pymc.io. Bug reports should still onto the Github issue tracker, but for all PyMC3 questions or modeling discussions, please use the discourse forum.

There are also some improvements to the documentation. Mainly, a quick-start to the general PyMC3 API, and a quick-start to the variational API.