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PRODID:-//pretalx//cfp.pydata.org//pydataglobal2025//speaker//79DLSQ
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UID:pretalx-pydataglobal2025-J9JCL9@cfp.pydata.org
DTSTART:20251210T160000Z
DTEND:20251210T163000Z
DESCRIPTION:We often must make decisions under uncertainty—should you car
 ry an umbrella if there's a 30 % chance of rain? Bayesian decision theor
 y provides a principled\, probabilistic framework to answer such questions
  by combining beliefs (probabilities)\, utilities (what matters to us)\, a
 nd actions to maximize expected gain.\n\nThis talk:\n- Introduces key deci
 sion‑theoretic concepts in intuitive terms.\n- Uses a toy umbrella examp
 le to ground ideas in relatable context.\n- Demonstrates applications in B
 ayesian optimization (PoI/EI) and Bayesian experimental design.\n- Is hand
 s‑on—with Python code and practical tools—so participants leave read
 y to apply these ideas to real‑world problems.
DTSTAMP:20260719T010405Z
LOCATION:Analytics\, Visualization & Decision Science
SUMMARY:Decisions Under Uncertainty: A Hands‑On Guide to Bayesian Decisio
 n Theory - Quan Nguyen
URL:https://cfp.pydata.org/pydataglobal2025/talk/J9JCL9/
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