Introduction

Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!

Folks, there are some new cool kids on the block. They are called PyMC, Aeppl, and Aesara, and it’s high time we give us a proper welcome!

To do that, who better than one of the architects of the new PyMC 4.0 — Ricardo Vieira! In this episode, he’ll walk us through the inner workings of the newly released version of PyMC, telling us why the Aesara backend and the brand new RandomVariable operators constitute such strong foundations for your beloved PyMC models. He will also tell us about a self-contained PPL project called Aeppl, dedicated to converting model graphs to probability functions — pretty cool, right?

Oh, in case you didn’t guess yet, Ricardo is a PyMC developer and data scientist at PyMC Labs. He spent several years teaching himself Statistics and Computer Science at the expense of his official degrees in Psychology and Neuroscience.

So, get ready for efficient random generator functions, better probability evaluation functions, and a fully-fledged modern Bayesian workflow!

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, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, 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, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Lin Yu Sha and Scott Anthony Robson.

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

Links from the show:

• Ricardo on Twitter: https://twitter.com/RicardoV944
• Ricardo on GitHub: https://github.com/ricardoV94/
• Ricardo’s website: https://ricardov94.github.io/posts/
• PyMC, Aesara and Aeppl: The New Kids on The Block (YouTube video): https://www.youtube.com/watch?v=_APNiXTfYJw
• Bayesian Vector Autoregression in PyMC: https://www.pymc-labs.io/blog-posts/bayesian-vector-autoregression/
• New PyMC website: https://www.pymc.io/projects/docs/en/stable/learn.html
• Define, optimize, and evaluate mathematical expressions with Aesara: https://aesara.readthedocs.io/en/latest/
• Aeppl documentation: https://aeppl.readthedocs.io/en/latest/
• PyMC’s YouTube channel: https://www.youtube.com/c/PyMCDevelopers
• PyMC on Twitter: https://twitter.com/pymc_devs
• PyMC on LinkedIn: https://www.linkedin.com/company/pymc/mycompany/
• LBS #61, Why we still use non-Bayesian methods, with EJ Wagenmakers: https://www.learnbayesstats.com/episode/61-why-we-still-use-non-bayesian-methods-ej-wagenmakers
• LBS #31, Bayesian Cognitive Modeling & Decision-Making, with Michael Lee:  https://www.learnbayesstats.com/episode/31-bayesian-cognitive-modeling-michael-lee
• We Have No Idea, A Guide to the Unknown Universe: https://www.amazon.com/We-Have-No-Idea-Universe/dp/0735211515