Learning Bayesian Statistics

A podcast by Alexandre Andorra - Wednesdays

Wednesdays

Categories:

141 Episodes

  1. #78 Exploring MCMC Sampler Algorithms, with Matt D. Hoffman

    Published: 3/1/2023
  2. #77 How a Simple Dress Helped Uncover Hidden Prejudices, with Pascal Wallisch

    Published: 2/13/2023
  3. #76 The Past, Present & Future of Stan, with Bob Carpenter

    Published: 2/1/2023
  4. #75 The Physics of Top Gun 2 Maverick, with Jason Berndt

    Published: 1/20/2023
  5. #74 Optimizing NUTS and Developing the ZeroSumNormal Distribution, with Adrian Seyboldt

    Published: 1/5/2023
  6. #73 A Guide to Plotting Inferences & Uncertainties of Bayesian Models, with Jessica Hullman

    Published: 12/23/2022
  7. #72 Why the Universe is so Deliciously Crazy, with Daniel Whiteson

    Published: 12/3/2022
  8. #71 Artificial Intelligence, Deepmind & Social Change, with Julien Cornebise

    Published: 11/14/2022
  9. #70 Teaching Bayes for Biology & Biological Engineering, with Justin Bois

    Published: 10/22/2022
  10. #69 Why, When & How to use Bayes Factors, with Jorge Tendeiro

    Published: 10/5/2022
  11. #68 Probabilistic Machine Learning & Generative Models, with Kevin Murphy

    Published: 9/14/2022
  12. #67 Exoplanets, Cool Worlds & Life in the Universe, with David Kipping

    Published: 8/31/2022
  13. #66 Uncertainty Visualization & Usable Stats, with Matthew Kay

    Published: 8/17/2022
  14. #65 PyMC, Aeppl, & Aesara: the new cool kids on the block, with Ricardo Vieira

    Published: 8/3/2022
  15. #64 Modeling the Climate & Gravity Waves, with Laura Mansfield

    Published: 7/20/2022
  16. #63 Media Mix Models & Bayes for Marketing, with Luciano Paz

    Published: 6/28/2022
  17. #62 Bayesian Generative Modeling for Healthcare, with Maria Skoularidou

    Published: 6/8/2022
  18. #61 Why we still use non-Bayesian methods, with EJ Wagenmakers

    Published: 5/19/2022
  19. #60 Modeling Dialogues & Languages, with J.P. de Ruiter

    Published: 4/30/2022
  20. #59 Bayesian Modeling in Civil Engineering, with Michael Faber

    Published: 4/14/2022

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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!