Today’s clip is from <a href="https://learnbayesstats.com/episode/129-bayesian-deep-learning-ai-for-science-vincent-fortuin" rel="noopener noreferrer" target="_blank">episode 129</a> of the podcast, with AI expert and researcher Vincent Fortuin.This conversation delves into the intricacies of Bayesian deep learning, contrasting it with traditional deep learning and exploring its applications and challenges.Get the full discussion at https://learnbayesstats.com/episode/129-bayesian-deep-learning-ai-for-science-vincent-fortuin<ul><li><a href="https://topmate.io/alex_andorra/503302" rel="noopener noreferrer" target="_blank">Intro to Bayes Course</a> (first 2 lessons free)</li><li><a href="https://topmate.io/alex_andorra/1011122" rel="noopener noreferrer" target="_blank">Advanced Regression Course</a> (first 2 lessons free)</li></ul> Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his <a href="https://bababrinkman.com/" rel="noopener noreferrer" target="_blank">awesome work</a>!Visit our <a href="https://www.patreon.com/learnbayesstats" rel="noopener noreferrer" target="_blank">Patreon page</a> to unlock exclusive Bayesian swag ;)TranscriptThis is an automatic transcript and may therefore contain errors. Please <a href="http://twitter.com/LearnBayesStats" rel="noopener noreferrer" target="_blank">get in touch</a> if you're willing to correct them.

Today’s clip is from episode 129 of the podcast, with AI expert and researcher Vincent Fortuin. This conversation delves into the intricacies of Bayesian deep learning, contrasting it with traditional deep learning and exploring its applications and challenges. Get the full discussion at https://learnbayesstats.com/episode/129-bayesian-deep-learning-ai-for-science-vincent-fortuinIntro to Bayes Course (first 2 lessons free)Advanced Regression Course (first 2 lessons free) Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work! Visit our Patreon page to unlock exclusive Bayesian swag ;) TranscriptThis is an automatic transcript and may therefore contain errors. Please get in touch if you're willing to correct them.

Today’s clip is from <a href="https://learnbayesstats.com/episode/129-bayesian-deep-learning-ai-for-science-vincent-fortuin" rel="noopener noreferrer">episode 129</a> of the podcast, with AI expert and researcher Vincent Fortuin.This conversation delves into the intricacies of Bayesian deep learning, contrasting it with traditional deep learning and exploring its applications and challenges.Get the full discussion at https://learnbayesstats.com/episode/129-bayesian-deep-learning-ai-for-science-vincent-fortuin<ul><li><a href="https://topmate.io/alex_andorra/503302" rel="noopener noreferrer">Intro to Bayes Course</a> (first 2 lessons free)</li><li><a href="https://topmate.io/alex_andorra/1011122" rel="noopener noreferrer">Advanced Regression Course</a> (first 2 lessons free)</li></ul> Our&nbsp;theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and&nbsp;Mega Ran). Check out his <a href="https://bababrinkman.com/" rel="noopener noreferrer">awesome work</a>!Visit our <a href="https://www.patreon.com/learnbayesstats" rel="noopener noreferrer">Patreon page</a> to unlock exclusive Bayesian swag ;)TranscriptThis is an automatic transcript and may therefore contain errors. Please <a href="http://twitter.com/LearnBayesStats" rel="noopener noreferrer">get in touch</a> if you're willing to correct them.

BITESIZE | The Why & How of Bayesian Deep Learning, with Vincent Fortuin

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 https://www.pymc-labs.io/ (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 https://docs.pymc.io/ (PyMC) and https://arviz-devs.github.io/arviz/ (ArviZ). I also love https://www.pollsposition.com/ (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 https://www.patreon.com/learnbayesstats (unlock exclusive Bayesian swag on Patreon)!

Science

Technology

Education

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 https://www.pymc-labs.io/ (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 https://docs.pymc.io/ (PyMC) and https://arviz-devs.github.io/arviz/ (ArviZ). I also love https://www.pollsposition.com/ (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 https://www.patreon.com/learnbayesstats (unlock exclusive Bayesian swag on Patreon)!

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BITESIZE | The Why & How of Bayesian Deep Learning, with Vincent Fortuin

BITESIZE | The Why & How of Bayesian Deep Learning, with Vincent Fortuin

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