Learning Bayesian Statistics

Un pódcast de Alexandre Andorra

Categorías:

132 Episodo

  1. #69 Why, When & How to use Bayes Factors, with Jorge Tendeiro

    Publicado: 5/10/2022
  2. #68 Probabilistic Machine Learning & Generative Models, with Kevin Murphy

    Publicado: 14/9/2022
  3. #67 Exoplanets, Cool Worlds & Life in the Universe, with David Kipping

    Publicado: 31/8/2022
  4. #66 Uncertainty Visualization & Usable Stats, with Matthew Kay

    Publicado: 17/8/2022
  5. #65 PyMC, Aeppl, & Aesara: the new cool kids on the block, with Ricardo Vieira

    Publicado: 3/8/2022
  6. #64 Modeling the Climate & Gravity Waves, with Laura Mansfield

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

    Publicado: 28/6/2022
  8. #62 Bayesian Generative Modeling for Healthcare, with Maria Skoularidou

    Publicado: 8/6/2022
  9. #61 Why we still use non-Bayesian methods, with EJ Wagenmakers

    Publicado: 19/5/2022
  10. #60 Modeling Dialogues & Languages, with J.P. de Ruiter

    Publicado: 30/4/2022
  11. #59 Bayesian Modeling in Civil Engineering, with Michael Faber

    Publicado: 14/4/2022
  12. #58 Bayesian Modeling and Computation, with Osvaldo Martin, Ravin Kumar and Junpeng Lao

    Publicado: 21/3/2022
  13. #57 Forecasting French Elections, with… Mystery Guest

    Publicado: 3/3/2022
  14. #56 Causal & Probabilistic Machine Learning, with Robert Osazuwa Ness

    Publicado: 16/2/2022
  15. #55 Neuropsychology, Illusions & Bending Reality, with Dominique Makowski

    Publicado: 31/1/2022
  16. #54 Bayes in Theoretical Ecology, with Florian Hartig

    Publicado: 14/1/2022
  17. #53 Bayesian Stats for the Behavioral & Neural Sciences, with Todd Hudson

    Publicado: 28/12/2021
  18. #52 Election forecasting models in Germany, with Marcus Gross

    Publicado: 9/12/2021
  19. #51 Bernoulli’s Fallacy & the Crisis of Modern Science, with Aubrey Clayton

    Publicado: 22/11/2021
  20. #50 Ta(l)king Risks & Embracing Uncertainty, with David Spiegelhalter

    Publicado: 6/11/2021

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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!

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