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VERSION:2.0
PRODID:-//pretalx//global2022.pydata.org//LRRXLV
BEGIN:VEVENT
UID:pretalx-cfp-LRRXLV@global2022.pydata.org
DTSTART:20221201T150000Z
DTEND:20221201T163000Z
DESCRIPTION:This tutorial is a hands-on introduction to Bayesian Decision A
nalysis (BDA)\, which is a framework for using probability to guide decisi
on-making under uncertainty. I start with Bayes's Theorem\, which is the f
oundation of Bayesian statistics\, and work toward the Bayesian bandit str
ategy\, which is used for A/B testing\, medical tests\, and related applic
ations. For each step\, I provide a Jupyter notebook where you can run Pyt
hon code and work on exercises. In addition to the bandit strategy\, I sum
marize two other applications of BDA\, optimal bidding and deriving a deci
sion rule. Finally\, I suggest resources you can use to learn more.
DTSTAMP:20240225T120115Z
LOCATION:Workshop/Tutorial I
SUMMARY:Bayesian Decision Analysis - Allen Downey
URL:https://global2022.pydata.org/cfp/talk/LRRXLV/
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