I’m excited to have had my first conference talk accepted, Learning Bayesian Statistics with Pokemon GO at PyMCon!

PyMCon is a virtual conference for the Bayesian community. While organized by the PyMC3 developers, the conference anyone interested in general-purpose Bayesian inference.

I’ve been immersed in the Bayesian inference world for a year now, so I saw a small conference as a great venue to submit my first proposal. I found out yesterday that I had been accepted!

My submission was for a “Let’s Build a Model” presentation titled Learning Bayesian Statistics with Pokemon GO. In the presentation, I’ll walk the audience through building a couple of Bayesian models to answer questions that the Pokemon GO player base has had.

The abstract:

In the mobile game Pokemon GO, players can rarely encounter “shiny” Pokemon. The exact appearance rates are unknown. But by using Bayesian inference and PyMC3, we can model different species’ shiny rates. In this beginner-level tutorial, we will introduce fundamental principles at the heart of Bayesian modeling; then we will apply them to develop PyMC3 models that can answer questions about Pokemon GO.

Stay tuned for updates!