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#75 The Physics of Top Gun 2 Maverick, with Jason Berndt

#75 The Physics of Top Gun 2 Maverick, with Jason Berndt

FromLearning Bayesian Statistics


#75 The Physics of Top Gun 2 Maverick, with Jason Berndt

FromLearning Bayesian Statistics

ratings:
Length:
67 minutes
Released:
Jan 20, 2023
Format:
Podcast episode

Description

Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!If you’re a nerd like me, you’re always curious about the physics of any situation. So, obviously, when I watched Top Gun 2, I became fascinated by the aerodynamics of fighters jets. And it so happens that one of my friends used to be a fighter pilot for the Canadian army… Immediately, I thought this would make for a cool episode — and here we are!Actually, Jason Berndt wanted to be a pilot from the age of 3. When he was 6, he went to an air show, and then specifically wanted to become a fighter pilot. In his teens, he learned how to fly saliplanes, small single engine aircrafts. At age 22, he got a bachelor’s in aero engineering from the royal military college, and then — well, he’ll tell you the rest in the episode.Now in his thirties, he owns real estate and created his own company, My Two Brows, selling temporary eyebrow tattoos — which, weirdly enough, is actually related to his time in the army…In his free time, Jason plays the guitar, travels around the world (that’s actually how we met), and loves chasing adrenaline however he can (paragliding, scuba diving, you name it!).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, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bert≈rand 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, 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, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin and Raphaël R.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:My Two Brows website: https://mytwobrows.com/My Two Brows on Instagram: https://www.instagram.com/my_two_brows/My Two Brows on YouTube:
Released:
Jan 20, 2023
Format:
Podcast episode

Titles in the series (100)

Are you a researcher or data scientist / analyst / ninja? Do you want to learn Bayesian inference, stay up to date or simply want to understand what Bayesian inference is? Then this podcast is for you! You'll hear from researchers and practitioners of all fields about how they use Bayesian statistics, and how in turn YOU can apply these methods in your modeling workflow. When I started learning Bayesian methods, I really wished there were a podcast out there that could introduce me to the methods, the projects and the people who make all that possible. So I created "Learning Bayesian Statistics", where you'll get to hear how Bayesian statistics are used to detect black matter in outer space, forecast elections or understand how diseases spread and can ultimately be stopped. But this show is not only about successes -- it's also about failures, because that's how we learn best. So you'll often hear the guests talking about what *didn't* work in their projects, why, and how they overcame these challenges. Because, in the end, we're all lifelong learners! My name is Alex Andorra by the way, and I live in Paris. By day, I'm a data scientist and modeler at the https://www.pymc-labs.io/ (PyMC Labs) consultancy. By night, I don't (yet) fight crime, but I'm an open-source enthusiast and core contributor to the python packages https://docs.pymc.io/ (PyMC) and https://arviz-devs.github.io/arviz/ (ArviZ). I also love https://www.pollsposition.com/ (election forecasting) and, most importantly, Nutella. But I don't like talking about it – I prefer eating it. So, whether you want to learn Bayesian statistics or hear about the latest libraries, books and applications, this podcast is for you -- just subscribe! You can also support the show and https://www.patreon.com/learnbayesstats (unlock exclusive Bayesian swag on Patreon)! This podcast uses the following third-party services for analysis: Podcorn - https://podcorn.com/privacy