Episode 32

#32 Getting involved into Bayesian Stats & Open-Source Development, with Peadar Coyle

When explaining Bayesian statistics to people who don’t know anything about stats, I often say that MCMC is about walking many different paths in lots of parallel universes, and then counting what happened in all these universes.

And in a sense, this whole podcast is dedicated to sampling the whole distribution of Bayesian practitioners. So, for this episode, I thought we’d take a break of pure, hard modeling and talk about how to get involved into Bayesian statistics and open-source development, how companies use Bayesian tools, and what common struggles and misperceptions the latter suffer from.

Quite the program, right? The good news is that Peadar Coyle, my guest for this episode, has done all of that! Coming to us from Armagh, Ireland, Peadar is a fellow PyMC core developer and was a data science and data engineer consultant until recently – a period during which he has covered all of modern startup data science, from AB testing to dashboards to data engineering to putting models into production.

From these experiences, Peadar has written a book consisting of numerous interviews with data scientists throughout the world – and do consider buying it, as money goes to the NumFOCUS organization, under which many Bayesian stats packages live, like Stan, ArviZ, PyMC, etc.

Now living in London, Peadar recently founded the start-up Aflorithmic, an AI solution that aims at developing personalized voice-first solutions for brands and enterprises. Their technology is also used to support children, families and elderly coping with the mental health challenges of COVID-19 confinements.

Before all that, Peadar studied physics, philosophy and mathematics at the universities of Bristol and Luxembourg. When he’s away from keyboard, he enjoys the outdoors, cooking and, of course, watching rugby!

Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !

Thank you to my Patrons for making this episode possible!

Yusuke Saito, Avi Bryant, Ero Carrera, Brian Huey, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, Demetri Pananos, James Ahloy, Jon Berezowski, Robin Taylor, Thomas Wiecki, Chad Scherrer, Vincent Arel-Bundock, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll and Nathaniel Burbank.

Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)

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About the Podcast

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Learning Bayesian Statistics
A podcast on Bayesian inference - the methods, the projects and the people who make it possible!

About your host

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Alexandre ANDORRA

Hi! I'm your host, Alex Andorra. By day, I'm a Bayesian modeler at the PyMC Labs consultancy. By night, I don't (yet) fight crime, but I'm an open-source enthusiast and core contributor to the awesome Python packages PyMC and ArviZ.

An always-learning statistician, I love building models and studying elections and human behavior. I also love Nutella a bit too much, but I don't like talking about it – I prefer eating it.

My goal is to make this podcast as interesting and useful to you as possible. So, hit me on Twitter or email with your questions and suggestions!