#26 What you’ll learn & who you’ll meet at the PyMC Conference, with Ravin Kumar & Quan Nguyen

Learning Bayesian Statistics

I don’t know about you, but I’m starting to really miss traveling and just talking to people without having to think about masks, social distance and activating the covid tracking app on my phone. In the coming days, there is one event that, granted, won’t make all of that disappear, but will remind me how enriching it is to meet new people — this event is PyMCon, the first-ever conference about the PyMC ecosystem! To talk about the conference format, goals and program, I had the pleasure to host Ravin Kumar and Quan Nguyen on the show.

Quan is a PhD student in computer science at Washington University in St Louis, USA, researching Bayesian machine learning and one of the PyMCon program committee chairs. He is also the author of several programming books on Python and scientific computing.

Ravin is a core contributor to Arviz and PyMC, and is leading the PyMCon conference. He holds a Bachelors in Mechanical Engineering and a Masters in Manufacturing Engineering. As a Principal Data Scientist he has used Bayesian Statistics to characterize and aid decision making at organizations like SpaceX and Sweetgreen. Ravin is also currently co-authoring a book with Ari Hartikainen, Osvaldo Martin, and Junpeng Lao on Bayesian Statistics due for release in February.

We talked about why they became involved in the conference, parsed through the numerous, amazing talks that are planned, and detailed who the keynote speakers will be… So, If you’re interested the link to register is in the show notes, and there are even two ways to get a free ticket: either by applying to a diversity scholarship, or by being a community partner, which is anyone or any organization working towards diversity and inclusion in tech — all links are in the show notes.

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

Links from the show:

• PyMCon speakers: https://pymc-devs.github.io/pymcon/speakers
• Register to PyMCon: https://www.eventbrite.com/e/pymcon-2020-tickets-121404065829
• PyMCon Diversity Scholarship: https://bit.ly/2J3Vb9d
• PyMCon Community Partner Form: https://bit.ly/35yq90L
• PyMC3 -- Probabilistic Programming in Python: https://docs.pymc.io
• Donate to PyMC3: https://numfocus.org/donate-to-pymc3
• PyMC3 for enterprise: https://bit.ly/3jo9jq9
• Ravin on Twitter: https://twitter.com/canyon289
• Quan on the web: https://krisnguyen135.github.io/
• Quan's author page: https://amzn.to/37JsB7r
• Alex talks about polls on the "Local Maximum" podcast: https://bit.ly/3e1Ro7O
• Support "Learning Bayesian Statistics" on Patreon: https://www.patreon.com/learnbayesstats

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 and Paul Oreto.