Learning Bayesian Statistics
En podcast af Alexandre Andorra - Onsdage
Kategorier:
145 Episoder
-
#98 Fusing Statistical Physics, Machine Learning & Adaptive MCMC, with Marylou Gabrié
Udgivet: 24.1.2024 -
Why Even Care About Science & Rationality
Udgivet: 20.1.2024 -
How To Get Into Causal Inference
Udgivet: 17.1.2024 -
#97 Probably Overthinking Statistical Paradoxes, with Allen Downey
Udgivet: 9.1.2024 -
How to Choose & Use Priors, with Daniel Lee
Udgivet: 20.12.2023 -
Becoming a Good Bayesian & Choosing Mentors, with Daniel Lee
Udgivet: 13.12.2023 -
#96 Pharma Models, Sports Analytics & Stan News, with Daniel Lee
Udgivet: 28.11.2023 -
#95 Unraveling Cosmic Mysteries, with Valerie Domcke
Udgivet: 15.11.2023 -
#94 Psychometrics Models & Choosing Priors, with Jonathan Templin
Udgivet: 24.10.2023 -
#93 A CERN Odyssey, with Kevin Greif
Udgivet: 18.10.2023 -
#92 How to Make Decision Under Uncertainty, with Gerd Gigerenzer
Udgivet: 4.10.2023 -
#91, Exploring European Football Analytics, with Max Göbel
Udgivet: 20.9.2023 -
#90, Demystifying MCMC & Variational Inference, with Charles Margossian
Udgivet: 6.9.2023 -
#89 Unlocking the Science of Exercise, Nutrition & Weight Management, with Eric Trexler
Udgivet: 23.8.2023 -
#88 Bridging Computation & Inference in Artificial Intelligent Systems, with Philipp Hennig
Udgivet: 10.8.2023 -
#87 Unlocking the Power of Bayesian Causal Inference, with Ben Vincent
Udgivet: 30.7.2023 -
#86 Exploring Research Synchronous Languages & Hybrid Systems, with Guillaume Baudart
Udgivet: 14.7.2023 -
#85 A Brief History of Sports Analytics, with Jim Albert
Udgivet: 27.6.2023 -
#84 Causality in Neuroscience & Psychology, with Konrad Kording
Udgivet: 13.6.2023 -
#83 Multilevel Regression, Post-Stratification & Electoral Dynamics, with Tarmo Jüristo
Udgivet: 25.5.2023
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!
