Learning Bayesian Statistics
Podcast autorstwa Alexandre Andorra
Kategorie:
132 Odcinki
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#49 The Present & Future of Baseball Analytics, with Ehsan Bokhari
Opublikowany: 22.10.2021 -
#48 Mixed Effects Models & Beautiful Plots, with TJ Mahr
Opublikowany: 8.10.2021 -
#47 Bayes in Physics & Astrophysics, with JJ Ruby
Opublikowany: 21.09.2021 -
#46 Silly & Empowering Statistics, with Chelsea Parlett-Pelleriti
Opublikowany: 30.08.2021 -
#45 Biostats & Clinical Trial Design, with Frank Harrell
Opublikowany: 10.08.2021 -
#44 Building Bayesian Models at scale, with Rémi Louf
Opublikowany: 22.07.2021 -
#43 Modeling Covid19, with Michael Osthege & Thomas Vladeck
Opublikowany: 8.07.2021 -
#42 How to Teach and Learn Bayesian Stats, with Mine Dogucu
Opublikowany: 24.06.2021 -
#41 Thinking Bayes, with Allen Downey
Opublikowany: 14.06.2021 -
#40 Bayesian Stats for the Speech & Language Sciences, with Allison Hilger and Timo Roettger
Opublikowany: 28.05.2021 -
#39 Survival Models & Biostatistics for Cancer Research, with Jacki Buros
Opublikowany: 14.05.2021 -
#38 How to Become a Good Bayesian (& Rap Artist), with Baba Brinkman
Opublikowany: 30.04.2021 -
#37 Prophet, Time Series & Causal Inference, with Sean Taylor
Opublikowany: 16.04.2021 -
#36 Bayesian Non-Parametrics & Developing Turing.jl, with Martin Trapp
Opublikowany: 30.03.2021 -
#35 The Past, Present & Future of BRMS, with Paul Bürkner
Opublikowany: 12.03.2021 -
#34 Multilevel Regression, Post-stratification & Missing Data, with Lauren Kennedy
Opublikowany: 25.02.2021 -
#33 Bayesian Structural Time Series, with Ben Zweig
Opublikowany: 12.02.2021 -
#32 Getting involved into Bayesian Stats & Open-Source Development, with Peadar Coyle
Opublikowany: 27.01.2021 -
#31 Bayesian Cognitive Modeling & Decision-Making, with Michael Lee
Opublikowany: 5.01.2021 -
#30 Symbolic Computation & Dynamic Linear Models, with Brandon Willard
Opublikowany: 18.12.2020
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!
