Learning Bayesian Statistics
Podcast tekijän mukaan Alexandre Andorra - Keskiviikkoisin
145 Jaksot
-
#62 Bayesian Generative Modeling for Healthcare, with Maria Skoularidou
Julkaistiin: 8.6.2022 -
#61 Why we still use non-Bayesian methods, with EJ Wagenmakers
Julkaistiin: 19.5.2022 -
#60 Modeling Dialogues & Languages, with J.P. de Ruiter
Julkaistiin: 30.4.2022 -
#59 Bayesian Modeling in Civil Engineering, with Michael Faber
Julkaistiin: 14.4.2022 -
#58 Bayesian Modeling and Computation, with Osvaldo Martin, Ravin Kumar and Junpeng Lao
Julkaistiin: 21.3.2022 -
#57 Forecasting French Elections, with… Mystery Guest
Julkaistiin: 3.3.2022 -
#56 Causal & Probabilistic Machine Learning, with Robert Osazuwa Ness
Julkaistiin: 16.2.2022 -
#55 Neuropsychology, Illusions & Bending Reality, with Dominique Makowski
Julkaistiin: 31.1.2022 -
#54 Bayes in Theoretical Ecology, with Florian Hartig
Julkaistiin: 14.1.2022 -
#53 Bayesian Stats for the Behavioral & Neural Sciences, with Todd Hudson
Julkaistiin: 28.12.2021 -
#52 Election forecasting models in Germany, with Marcus Gross
Julkaistiin: 9.12.2021 -
#51 Bernoulli’s Fallacy & the Crisis of Modern Science, with Aubrey Clayton
Julkaistiin: 22.11.2021 -
#50 Ta(l)king Risks & Embracing Uncertainty, with David Spiegelhalter
Julkaistiin: 6.11.2021 -
#49 The Present & Future of Baseball Analytics, with Ehsan Bokhari
Julkaistiin: 22.10.2021 -
#48 Mixed Effects Models & Beautiful Plots, with TJ Mahr
Julkaistiin: 8.10.2021 -
#47 Bayes in Physics & Astrophysics, with JJ Ruby
Julkaistiin: 21.9.2021 -
#46 Silly & Empowering Statistics, with Chelsea Parlett-Pelleriti
Julkaistiin: 30.8.2021 -
#45 Biostats & Clinical Trial Design, with Frank Harrell
Julkaistiin: 10.8.2021 -
#44 Building Bayesian Models at scale, with Rémi Louf
Julkaistiin: 22.7.2021 -
#43 Modeling Covid19, with Michael Osthege & Thomas Vladeck
Julkaistiin: 8.7.2021
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!
