While My MCMC Gently Samples

Bayesian modeling, Computational Psychiatry, and Python

What's new in PyMC3 3.1

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 …

Bayesian Deep Learning

Neural Networks in PyMC3 estimated with Variational Inference

(c) 2016 by Thomas Wiecki

There are currently three big trends in machine learning: Probabilistic Programming, Deep Learning and "Big Data". Inside of PP, a lot of innovation is in making things scale using Variational Inference. In …

MCMC sampling for dummies

When I give talks about probabilistic programming and Bayesian statistics, I usually gloss over the details of how inference is actually performed, treating it as a black box essentially. The beauty of probabilistic programming is that you actually don't have to understand how the inference works in order to build …

A modern guide to getting started with Data Science and Python

Python has an extremely rich and healthy ecosystem of data science tools. Unfortunately, to outsiders this ecosystem can look like a jungle (cue snake joke). In this blog post I will provide a step-by-step guide to venturing into this PyData jungle.

What's wrong with the many lists of PyData packages …