Learning Bayesian Statistics
A podcast by Alexandre Andorra - Wednesdays
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Categories:
141 Episodes
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#78 Exploring MCMC Sampler Algorithms, with Matt D. Hoffman
Published: 3/1/2023 -
#77 How a Simple Dress Helped Uncover Hidden Prejudices, with Pascal Wallisch
Published: 2/13/2023 -
#76 The Past, Present & Future of Stan, with Bob Carpenter
Published: 2/1/2023 -
#75 The Physics of Top Gun 2 Maverick, with Jason Berndt
Published: 1/20/2023 -
#74 Optimizing NUTS and Developing the ZeroSumNormal Distribution, with Adrian Seyboldt
Published: 1/5/2023 -
#73 A Guide to Plotting Inferences & Uncertainties of Bayesian Models, with Jessica Hullman
Published: 12/23/2022 -
#72 Why the Universe is so Deliciously Crazy, with Daniel Whiteson
Published: 12/3/2022 -
#71 Artificial Intelligence, Deepmind & Social Change, with Julien Cornebise
Published: 11/14/2022 -
#70 Teaching Bayes for Biology & Biological Engineering, with Justin Bois
Published: 10/22/2022 -
#69 Why, When & How to use Bayes Factors, with Jorge Tendeiro
Published: 10/5/2022 -
#68 Probabilistic Machine Learning & Generative Models, with Kevin Murphy
Published: 9/14/2022 -
#67 Exoplanets, Cool Worlds & Life in the Universe, with David Kipping
Published: 8/31/2022 -
#66 Uncertainty Visualization & Usable Stats, with Matthew Kay
Published: 8/17/2022 -
#65 PyMC, Aeppl, & Aesara: the new cool kids on the block, with Ricardo Vieira
Published: 8/3/2022 -
#64 Modeling the Climate & Gravity Waves, with Laura Mansfield
Published: 7/20/2022 -
#63 Media Mix Models & Bayes for Marketing, with Luciano Paz
Published: 6/28/2022 -
#62 Bayesian Generative Modeling for Healthcare, with Maria Skoularidou
Published: 6/8/2022 -
#61 Why we still use non-Bayesian methods, with EJ Wagenmakers
Published: 5/19/2022 -
#60 Modeling Dialogues & Languages, with J.P. de Ruiter
Published: 4/30/2022 -
#59 Bayesian Modeling in Civil Engineering, with Michael Faber
Published: 4/14/2022
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 Estonia. By day, I'm a data scientist and 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 python packages PyMC and ArviZ. I also love 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 unlock exclusive Bayesian swag on Patreon!