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šŸŽ™ļø Speaker: Chris Fonnesbeck, Thomas Wiecki | ā° Time: 16:00 UTC / 9am PT / 12pm ET / 6pm Berlin

Decision-making in sports has become increasingly data-driven with GPS, cameras, and other sensors providing streams of information at high spatial and temporal resolution. While machine learning is a popular approach for turning these data streams into actionable information, Bayesian statistical methods offer a robust alternative. They allow for the combining of multiple data sources, a natural means for imputing missing data, as well as full accounting for various system uncertainties.

In particular, hierarchical models provide a means for integrating information at multiple scales and adjusting for biases associated with small sample sizes. I will demonstrate a Bayesian workflow for model development using PyMC version 5, from data preparation through to the summarization of estimates and predictions, using baseball data.

šŸ“œ Outline of Talk / Agenda:

  • 5 min: Intro to PyMC Labs and speakers
  • 45 min: Presentation, panel discussion
  • 10 min: Q&A

šŸ’¼ About the speaker:

  1. Chris Fonnesbeck

Chris is the Principal Quantitative Analyst in Baseball Research & Development for the Philadelphia Phillies. He is interested in computational statistics, machine learning, Bayesian methods, and applied decision analysis. He hails from Vancouver, Canada and received his Ph.D. from the University of Georgia.​

šŸ”— Connect with Chris:
šŸ‘‰ LinkedIn: https://www.linkedin.com/in/christopher-fonnesbeck-374a492a/

2. Dr. Thomas Wiecki (PyMC Labs)

Dr. Thomas Wiecki is an author of PyMC, the leading platform for statistical data science. To help businesses solve some of their trickiest data science problems, he assembled a world-class team of Bayesian modelers and founded PyMC Labs -- the Bayesian consultancy. He did his PhD at Brown University studying cognitive neuroscience.

šŸ”— Connect with Thomas Wiecki:
šŸ‘‰ GitHub: https://github.com/twiecki
šŸ‘‰ Twitter: https://twitter.com/twiecki
šŸ‘‰ Website: https://twiecki.io/

šŸ“– Code of Conduct:
Please note that participants are expected to abide by PyMC's Code of Conduct.

šŸ”— Connecting with PyMC Labs:
šŸ‘„ LinkedIn: https://www.linkedin.com/company/pymc-labs/
🐦 Twitter: https://twitter.com/pymc_labs
šŸŽ„ YouTube: https://www.youtube.com/c/PyMCLabs
šŸ¤ Meetup: https://www.meetup.com/pymc-labs-online-meetup/

šŸ”— Connecting with PyMC Open Source:
šŸ’¬ Q&A/Discussion: https://discourse.pymc.io
šŸ™ GitHub: https://github.com/pymc-devs/pymc
šŸ’¼ LinkedIn: https://www.linkedin.com/company/pymc/mycompany
🐄 Twitter: https://twitter.com/pymc_devs
šŸ“ŗ YouTube: https://www.youtube.com/c/PyMCDevelopers
šŸŽ‰ Meetup: https://www.meetup.com/pymc-online-meetup/

Data Science
New Technology
Python
Open Source
Bayesian Statistics

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