# Variational Inference: Bayesian Neural Networks¶

(c) 2016-2018 by Thomas Wiecki, updated by Maxim Kochurov

Original blog post: https://twiecki.github.io/blog/2016/06/01/bayesian-deep-learning/

There are currently three big trends in machine learning: Probabilistic Programming, Deep Learning and "Big Data". Inside of PP …

# 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 …

# The best of both worlds: Hierarchical Linear Regression in PyMC3¶

(c) Thomas Wiecki & Danne Elbers 2020

The power of Bayesian modelling really clicked for me when I was first introduced to hierarchical modelling. In this blog post we will highlight the advantage of using hierarchical Bayesian modelling as opposed to …

# Easily distributing a parallel IPython Notebook on a cluster

Have you ever asked yourself: "Do I want to spend 2 days adjusting this analysis to run on the cluster and wait 2 days for the jobs to finish or do I just run it locally with no extra work and just wait a week."

If so, this blog post …

# Hammer time: Nailing the emcee ensemble sampler onto PyMC

tl;dr: I hacked the emcee--The MCMC-Hammer ensemble sampler to work on PyMC models.

## Motivation¶

PyMC is an awesome Python module to perform Bayesian inference. It allows for flexible model creation and has basic MCMC samplers like Metropolis-Hastings. The upcoming PyMC3 will feature much fancier samplers like Hamiltonian-Monte Carlo …

# This world is far from Normal(ly distributed): Bayesian Robust Regression in PyMC3

Author: Thomas Wiecki

This tutorial first appeard as a post in small series on Bayesian GLMs on my blog:

# The Inference Button: Bayesian GLMs made easy with PyMC3

Author: Thomas Wiecki

This tutorial appeared as a post in a small series on Bayesian GLMs on my blog: