Learning Bayesian Statistics
A podcast by Alexandre Andorra
Categories:
130 Episodes
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#87 Unlocking the Power of Bayesian Causal Inference, with Ben Vincent
Published: 30/07/2023 -
#86 Exploring Research Synchronous Languages & Hybrid Systems, with Guillaume Baudart
Published: 14/07/2023 -
#85 A Brief History of Sports Analytics, with Jim Albert
Published: 27/06/2023 -
#84 Causality in Neuroscience & Psychology, with Konrad Kording
Published: 13/06/2023 -
#83 Multilevel Regression, Post-Stratification & Electoral Dynamics, with Tarmo Jüristo
Published: 25/05/2023 -
#82 Sequential Monte Carlo & Bayesian Computation Algorithms, with Nicolas Chopin
Published: 5/05/2023 -
#81 Neuroscience of Perception: Exploring the Brain, with Alan Stocker
Published: 24/04/2023 -
#80 Bayesian Additive Regression Trees (BARTs), with Sameer Deshpande
Published: 11/04/2023 -
#79 Decision-Making & Cost Effectiveness Analysis for Health Economics, with Gianluca Baio
Published: 17/03/2023 -
#78 Exploring MCMC Sampler Algorithms, with Matt D. Hoffman
Published: 1/03/2023 -
#77 How a Simple Dress Helped Uncover Hidden Prejudices, with Pascal Wallisch
Published: 13/02/2023 -
#76 The Past, Present & Future of Stan, with Bob Carpenter
Published: 1/02/2023 -
#75 The Physics of Top Gun 2 Maverick, with Jason Berndt
Published: 20/01/2023 -
#74 Optimizing NUTS and Developing the ZeroSumNormal Distribution, with Adrian Seyboldt
Published: 5/01/2023 -
#73 A Guide to Plotting Inferences & Uncertainties of Bayesian Models, with Jessica Hullman
Published: 23/12/2022 -
#72 Why the Universe is so Deliciously Crazy, with Daniel Whiteson
Published: 3/12/2022 -
#71 Artificial Intelligence, Deepmind & Social Change, with Julien Cornebise
Published: 14/11/2022 -
#70 Teaching Bayes for Biology & Biological Engineering, with Justin Bois
Published: 22/10/2022 -
#69 Why, When & How to use Bayes Factors, with Jorge Tendeiro
Published: 5/10/2022 -
#68 Probabilistic Machine Learning & Generative Models, with Kevin Murphy
Published: 14/09/2022
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!