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DTSTART:20260329T030000
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SUMMARY:Is Your Data Lying? Bayesian Data Credibility - Vince Nelidov
DTSTART;TZID=Europe/Zurich:20261023T113500
DTEND;TZID=Europe/Zurich:20261023T120500
DTSTAMP:20261111T040114Z
UID:pretalx-swiss-python-summit-2026-3F9QQD@talks.python-summit.ch
DESCRIPTION:Datasets are often treated as ground truth\, even though they 
 rarely are. Labels can be noisy\, measurements can be imprecise\, user seg
 ments can be under-recorded\, and dashboards can hide uncertainty behind c
 lean-looking numbers. Teams then often build models\, metrics\, and decisi
 ons on top of data whose reliability we have never actually measured.\n\nT
 his talk shows how Bayesian modelling can make data credibility explicit. 
 Using simple\, realistic examples\, we will model uncertainty in labels\, 
 measurements\, and sampling bias\; distinguish signal from noise\; and ide
 ntify parts of a dataset that should not be trusted at face value. The goa
 l is to employ Bayesian statistics as a practical tool for asking: where i
 s this dataset solid\, where is it fragile\, and where might it be mislead
 ing us?\n\nAttendees will leave with a practical framework for measuring d
 ata trustworthiness\, and concrete examples of how Bayesian methods can ma
 ke uncertainty visible before it starts to contaminate models\, dashboards
 \, or business decisions.
LOCATION:Aula 4.101
URL:https://talks.python-summit.ch/swiss-python-summit-2026/talk/3F9QQD/
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