Chris Fonnesbeck's guest appearances

Chris Fonnesbeck

dats'n'stats

Learning Bayesian Statistics

David Spiegelhalter

Andrew Gelman

Michael Lee

Baba Brinkman

Kevin Systrom

Michael Kennedy

Travis Oliphant

Allen Downey

Sean Taylor

Michael Faber

Matthew Kay

Michael Betancourt

Eric Ma

Karin Knudson

Colin Carroll

OwlTail

When are Bayesian methods most useful? Conversely, when should you NOT use them? How do you teach them? What are the most important skills to pick-up when learning Bayes? And what are the most difficult topics, the ones you should maybe save for later?In this episode, you’ll hear Chris Fonnesbeck answer these questions from the perspective of marine biology and sports analytics. Chris is indeed the New York Yankees’ senior quantitative analyst and an associate professor at Vanderbilt University School of Medicine. He specializes in computational statistics, Bayesian methods, meta-analysis, and applied decision analysis. He also created PyMC, a library to do probabilistic programming in python, and is the author of several tutorials at PyCon and PyData conferences.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com!Links from the show:Chris on Twitter: https://twitter.com/fonnesbeckPyMC3, Probabilistic Programming in Python: https://docs.pymc.io/Chris on GitHub: https://github.com/fonnesbeckAn introduction to Markov Chain Monte Carlo using PyMC3 - PyData London 2019: https://www.youtube.com/watch?v=SS_pqgFziAgIntroduction to Statistical Modeling with Python - PyCon 2017 - video: https://www.youtube.com/watch?v=TMmSESkhRtIIntroduction to Statistical Modeling with Python - PyCon 2017 - code repo: https://github.com/fonnesbeck/intro_stat_modeling_2017Bayesian Non-parametric Models for Data Science using PyMC3 - PyCon 2018: https://www.youtube.com/watch?v=-sIOMs4MSuAStatistical Data Analysis in Python: https://github.com/fonnesbeck/statistical-analysis-python-tutorialThis podcast uses the following third-party services for analysis: Podcorn - https://podcorn.com/privacy

When are Bayesian methods most useful? Conversely, when should you NOT use them? How do you teach them? What are the most important skills to pick-up when learning Bayes? And what are the most difficult topics, the ones you should maybe save for later?In this episode, you’ll hear Chris Fonnesbeck answer these questions from the perspective of marine biology and sports analytics. Chris is indeed the New York Yankees’ senior quantitative analyst and an associate professor at Vanderbilt University School of Medicine. He specializes in computational statistics, Bayesian methods, meta-analysis, and applied decision analysis. He also created PyMC, a library to do probabilistic programming in python, and is the author of several tutorials at PyCon and PyData conferences.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at <a href="https://bababrinkman.com/" rel="noopener noreferrer nofollow" target="_blank">https://bababrinkman.com</a>!Links from the show:<ul><li>Chris on Twitter: <a href="https://twitter.com/fonnesbeck" rel="noopener noreferrer nofollow" target="_blank">https://twitter.com/fonnesbeck</a></li><li>PyMC3, Probabilistic Programming in Python: <a href="https://docs.pymc.io/" rel="noopener noreferrer nofollow" target="_blank">https://docs.pymc.io/</a></li><li>Chris on GitHub: <a href="https://github.com/fonnesbeck" rel="noopener noreferrer nofollow" target="_blank">https://github.com/fonnesbeck</a></li><li>An introduction to Markov Chain Monte Carlo using PyMC3 - PyData London 2019: <a href="https://www.youtube.com/watch?v=SS_pqgFziAg" rel="noopener noreferrer nofollow" target="_blank">https://www.youtube.com/watch?v=SS_pqgFziAg</a></li><li>Introduction to Statistical Modeling with Python - PyCon 2017 - video: <a href="https://www.youtube.com/watch?v=TMmSESkhRtI" rel="noopener noreferrer nofollow" target="_blank">https://www.youtube.com/watch?v=TMmSESkhRtI</a></li><li>Introduction to Statistical Modeling with Python - PyCon 2017 - code repo: <a href="https://github.com/fonnesbeck/intro_stat_modeling_2017" rel="noopener noreferrer nofollow" target="_blank">https://github.com/fonnesbeck/intro_stat_modeling_2017</a></li><li>Bayesian Non-parametric Models for Data Science using PyMC3 - PyCon 2018: <a href="https://www.youtube.com/watch?v=-sIOMs4MSuA" rel="noopener noreferrer nofollow" target="_blank">https://www.youtube.com/watch?v=-sIOMs4MSuA</a></li><li>Statistical Data Analysis in Python: <a href="https://github.com/fonnesbeck/statistical-analysis-python-tutorial" rel="noopener noreferrer nofollow" target="_blank">https://github.com/fonnesbeck/statistical-analysis-python-tutorial</a></li></ul>This podcast uses the following third-party services for analysis: Podcorn - <a href="https://podcorn.com/privacy" rel="nofollow" target="_blank">https://podcorn.com/privacy</a>

#2 When should you use Bayesian tools, and Bayes in sports analytics, with Chris Fonnesbeck

I am beyond excited to share this first episode of the PyData podcast with you. The idea is to have a free-form discussion with interesting guests which does not shy away from more advanced topics.In this episode I talk to Chris Fonnesbeck: Professor for biostatistics at Vanderbilt University and, as of recent, Data Scientist at the New York Yankees. We start off this discussion by talking about Bayesian statistics, probabilistic programming. Chris then talks about the history of PyMC and what the current status of PyMC4 is.We then dive more into his background and how he moved from marine biology to become a data scientist in sports analytics and the lessons he learned along the way.Special thanks to my Patreons Andrew Ng, Daniel Gerlanc, and Richard Craib.If you would like to support the podcast go to: https://patreon.com/twieckiFollow Chris on Twitter: https://twitter.com/fonnesbeckSupport the show

I am beyond excited to share this first episode of the PyData podcast with you. The idea is to have a free-form discussion with interesting guests which does not shy away from more advanced topics. In this episode I talk to Chris Fonnesbeck: Professor for biostatistics at Vanderbilt University and, as of recent, Data Scientist at the New York Yankees. We start off this discussion by talking about Bayesian statistics, probabilistic programming. Chris then talks about the history of PyMC and what the current status of PyMC4 is. We then dive more into his background and how he moved from marine biology to become a data scientist in sports analytics and the lessons he learned along the way. Special thanks to my Patreons Andrew Ng, Daniel Gerlanc, and Richard Craib. If you would like to support the podcast go to: <a href="https://www.patreon.com/twiecki" rel="nofollow" target="_blank">https://patreon.com/twiecki</a> Follow Chris on Twitter: <a href="https://twitter.com/fonnesbeck" rel="nofollow" target="_blank">https://twitter.com/fonnesbeck</a><a href="https://www.patreon.com/twiecki" rel="payment nofollow" target="_blank">Support the show</a>

Chris Fonnesbeck - Probabilistic Programming