Learning Bayesian Statistics
Podcast autorstwa Alexandre Andorra
Kategorie:
132 Odcinki
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#69 Why, When & How to use Bayes Factors, with Jorge Tendeiro
Opublikowany: 5.10.2022 -
#68 Probabilistic Machine Learning & Generative Models, with Kevin Murphy
Opublikowany: 14.09.2022 -
#67 Exoplanets, Cool Worlds & Life in the Universe, with David Kipping
Opublikowany: 31.08.2022 -
#66 Uncertainty Visualization & Usable Stats, with Matthew Kay
Opublikowany: 17.08.2022 -
#65 PyMC, Aeppl, & Aesara: the new cool kids on the block, with Ricardo Vieira
Opublikowany: 3.08.2022 -
#64 Modeling the Climate & Gravity Waves, with Laura Mansfield
Opublikowany: 20.07.2022 -
#63 Media Mix Models & Bayes for Marketing, with Luciano Paz
Opublikowany: 28.06.2022 -
#62 Bayesian Generative Modeling for Healthcare, with Maria Skoularidou
Opublikowany: 8.06.2022 -
#61 Why we still use non-Bayesian methods, with EJ Wagenmakers
Opublikowany: 19.05.2022 -
#60 Modeling Dialogues & Languages, with J.P. de Ruiter
Opublikowany: 30.04.2022 -
#59 Bayesian Modeling in Civil Engineering, with Michael Faber
Opublikowany: 14.04.2022 -
#58 Bayesian Modeling and Computation, with Osvaldo Martin, Ravin Kumar and Junpeng Lao
Opublikowany: 21.03.2022 -
#57 Forecasting French Elections, with… Mystery Guest
Opublikowany: 3.03.2022 -
#56 Causal & Probabilistic Machine Learning, with Robert Osazuwa Ness
Opublikowany: 16.02.2022 -
#55 Neuropsychology, Illusions & Bending Reality, with Dominique Makowski
Opublikowany: 31.01.2022 -
#54 Bayes in Theoretical Ecology, with Florian Hartig
Opublikowany: 14.01.2022 -
#53 Bayesian Stats for the Behavioral & Neural Sciences, with Todd Hudson
Opublikowany: 28.12.2021 -
#52 Election forecasting models in Germany, with Marcus Gross
Opublikowany: 9.12.2021 -
#51 Bernoulli’s Fallacy & the Crisis of Modern Science, with Aubrey Clayton
Opublikowany: 22.11.2021 -
#50 Ta(l)king Risks & Embracing Uncertainty, with David Spiegelhalter
Opublikowany: 6.11.2021
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!
