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TZID:Europe/Paris
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SUMMARY:Catching ML mistakes automatically with skore: from data scientist
 s to agentic pipelines - Gaetan de Castellane
DTSTART;TZID=Europe/Paris:20261125T112500
DTEND;TZID=Europe/Paris:20261125T115500
DTSTAMP:20260930T120806Z
UID:pretalx-compute-paris-2026-P7GK3M@pretalx.com
DESCRIPTION:Skore is an open source machine learning library that helps da
 ta scientists evaluate models and apply recommended practices throughout t
 he ML development lifecycle. This talk dives into one of its core features
 : "checks\," automated diagnostics that run on any scikit-learn-compatible
  estimator and flag issues with stable\, actionable error codes. We'll see
  how checks catch common modeling pitfalls out of the box\, how teams can 
 write custom checks to encode their own business and compliance requiremen
 ts\, and how their structured output makes them a natural fit for agentic 
 ML development loops.
LOCATION:Auditorium
URL:https://pretalx.com/compute-paris-2026/talk/P7GK3M/
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