Learning Bayesian Statistics
Podcast autorstwa Alexandre Andorra
Kategorie:
132 Odcinki
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#29 Model Assessment, Non-Parametric Models, And Much More, with Aki Vehtari
Opublikowany: 2.12.2020 -
#28 Game Theory, Industrial Organization & Policy Design, with Shosh Vasserman
Opublikowany: 20.11.2020 -
#27 Modeling the US Presidential Elections, with Andrew Gelman & Merlin Heidemanns
Opublikowany: 1.11.2020 -
#26 What you’ll learn & who you’ll meet at the PyMC Conference, with Ravin Kumar & Quan Nguyen
Opublikowany: 24.10.2020 -
#25 Bayesian Stats in Football Analytics, with Kevin Minkus
Opublikowany: 9.10.2020 -
#24 Bayesian Computational Biology in Julia, with Seth Axen
Opublikowany: 24.09.2020 -
#23 Bayesian Stats in Business and Marketing Analytics, with Elea McDonnel Feit
Opublikowany: 10.09.2020 -
#22 Eliciting Priors and Doing Bayesian Inference at Scale, with Avi Bryant
Opublikowany: 26.08.2020 -
#21 Gaussian Processes, Bayesian Neural Nets & SIR Models, with Elizaveta Semenova
Opublikowany: 13.08.2020 -
#20 Regression and Other Stories, with Andrew Gelman, Jennifer Hill & Aki Vehtari
Opublikowany: 30.07.2020 -
#19 Turing, Julia and Bayes in Economics, with Cameron Pfiffer
Opublikowany: 3.07.2020 -
#SpecialAnnouncement: Patreon Launched!
Opublikowany: 26.06.2020 -
#18 How to ask good Research Questions and encourage Open Science, with Daniel Lakens
Opublikowany: 18.06.2020 -
#17 Reparametrize Your Models Automatically, with Maria Gorinova
Opublikowany: 4.06.2020 -
#16 Bayesian Statistics the Fun Way, with Will Kurt
Opublikowany: 21.05.2020 -
#15 The role of Python in Science and Education, with Michael Kennedy
Opublikowany: 6.05.2020 -
#14 Hidden Markov Models & Statistical Ecology, with Vianey Leos-Barajas
Opublikowany: 22.04.2020 -
#13 Building a Probabilistic Programming Framework in Julia, with Chad Scherrer
Opublikowany: 8.04.2020 -
#12 Biostatistics and Differential Equations, with Demetri Pananos
Opublikowany: 25.03.2020 -
#11 Taking care of your Hierarchical Models, with Thomas Wiecki
Opublikowany: 11.03.2020
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!
