Learning Bayesian Statistics

En podcast av Alexandre Andorra - Onsdagar

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  1. #106 Active Statistics, Two Truths & a Lie, with Andrew Gelman

    Publicerades: 2024-05-16
  2. #105 The Power of Bayesian Statistics in Glaciology, with Andy Aschwanden & Doug Brinkerhoff

    Publicerades: 2024-05-02
  3. #104 Automated Gaussian Processes & Sequential Monte Carlo, with Feras Saad

    Publicerades: 2024-04-16
  4. #103 Improving Sampling Algorithms & Prior Elicitation, with Arto Klami

    Publicerades: 2024-04-05
  5. #102 Bayesian Structural Equation Modeling & Causal Inference in Psychometrics, with Ed Merkle

    Publicerades: 2024-03-20
  6. How to find black holes with Bayesian inference

    Publicerades: 2024-03-16
  7. How can we even hear gravitational waves?

    Publicerades: 2024-03-14
  8. #101 Black Holes Collisions & Gravitational Waves, with LIGO Experts Christopher Berry & John Veitch

    Publicerades: 2024-03-07
  9. The Role of Variational Inference in Reactive Message Passing

    Publicerades: 2024-03-01
  10. Reactive Message Passing in Bayesian Inference

    Publicerades: 2024-02-28
  11. #100 Reactive Message Passing & Automated Inference in Julia, with Dmitry Bagaev

    Publicerades: 2024-02-21
  12. The biggest misconceptions about Bayes & Quantum Physics

    Publicerades: 2024-02-16
  13. Why would you use Bayesian Statistics?

    Publicerades: 2024-02-14
  14. #99 Exploring Quantum Physics with Bayesian Stats, with Chris Ferrie

    Publicerades: 2024-02-09
  15. How do sampling algorithms scale?

    Publicerades: 2024-02-05
  16. Why choose new algorithms instead of HMC?

    Publicerades: 2024-02-04
  17. #98 Fusing Statistical Physics, Machine Learning & Adaptive MCMC, with Marylou Gabrié

    Publicerades: 2024-01-24
  18. Why Even Care About Science & Rationality

    Publicerades: 2024-01-20
  19. How To Get Into Causal Inference

    Publicerades: 2024-01-17
  20. #97 Probably Overthinking Statistical Paradoxes, with Allen Downey

    Publicerades: 2024-01-09

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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!

Visit the podcast's native language site