Learning Bayesian Statistics
En podcast av Alexandre Andorra - Onsdagar
Kategorier:
141 Avsnitt
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#38 How to Become a Good Bayesian (& Rap Artist), with Baba Brinkman
Publicerades: 2021-04-30 -
#37 Prophet, Time Series & Causal Inference, with Sean Taylor
Publicerades: 2021-04-16 -
#36 Bayesian Non-Parametrics & Developing Turing.jl, with Martin Trapp
Publicerades: 2021-03-30 -
#35 The Past, Present & Future of BRMS, with Paul Bürkner
Publicerades: 2021-03-12 -
#34 Multilevel Regression, Post-stratification & Missing Data, with Lauren Kennedy
Publicerades: 2021-02-25 -
#33 Bayesian Structural Time Series, with Ben Zweig
Publicerades: 2021-02-12 -
#32 Getting involved into Bayesian Stats & Open-Source Development, with Peadar Coyle
Publicerades: 2021-01-27 -
#31 Bayesian Cognitive Modeling & Decision-Making, with Michael Lee
Publicerades: 2021-01-05 -
#30 Symbolic Computation & Dynamic Linear Models, with Brandon Willard
Publicerades: 2020-12-18 -
#29 Model Assessment, Non-Parametric Models, And Much More, with Aki Vehtari
Publicerades: 2020-12-02 -
#28 Game Theory, Industrial Organization & Policy Design, with Shosh Vasserman
Publicerades: 2020-11-20 -
#27 Modeling the US Presidential Elections, with Andrew Gelman & Merlin Heidemanns
Publicerades: 2020-11-01 -
#26 What you’ll learn & who you’ll meet at the PyMC Conference, with Ravin Kumar & Quan Nguyen
Publicerades: 2020-10-24 -
#25 Bayesian Stats in Football Analytics, with Kevin Minkus
Publicerades: 2020-10-09 -
#24 Bayesian Computational Biology in Julia, with Seth Axen
Publicerades: 2020-09-24 -
#23 Bayesian Stats in Business and Marketing Analytics, with Elea McDonnel Feit
Publicerades: 2020-09-10 -
#22 Eliciting Priors and Doing Bayesian Inference at Scale, with Avi Bryant
Publicerades: 2020-08-26 -
#21 Gaussian Processes, Bayesian Neural Nets & SIR Models, with Elizaveta Semenova
Publicerades: 2020-08-13 -
#20 Regression and Other Stories, with Andrew Gelman, Jennifer Hill & Aki Vehtari
Publicerades: 2020-07-30 -
#19 Turing, Julia and Bayes in Economics, with Cameron Pfiffer
Publicerades: 2020-07-03
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!
