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UID:pretalx-euroscipy-2026-VXRSM8@pretalx.com
DTSTART;TZID=CET:20260720T143000
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DESCRIPTION:This talk will introduce scikit-learn users to the new API for 
 metadata routing\, a feature introduced in the recent releases available i
 n experimental mode. As a scikit-learn core developer\, I'll share insight
 s from my experience working directly on this feature.\n\nWe will explore 
 what metadata is\, how it can be used in machine learning pipelines\, and 
 how the new API simplifies routing metadata throughout a workflow. Routing
  metadata refers to an internal mechanism to pass metadata around between 
 components of a data science pipeline\, ensuring it reaches the functions 
 that consume or utilize it.\n\nUsing well-known metadata such as sample_we
 ight and groups which are implemented in many scikit-learn metrics and eva
 luation tools\, we will examine the restrictions for passing metadata prio
 r to the introduction of the new API. Then\, we will enable the new routin
 g API and demonstrate how it solves these challenges with examples that in
 volve layers of nested-ness through cross-validation\, hyperparameter tuni
 ng\, or pipelines. We will explain the core components of the API\, includ
 ing methods like set_fit_request() and how to actually pass our metadata.\
 n\nAttendees will leave with an understanding of how to enable and use the
  new routing API including passing metadata through Pipeline objects and v
 alidation tools like cross_validate. Additional references to the metadata
  user guide and developer guide will be provided for those interested in f
 urther exploration.
DTSTAMP:20260603T195654Z
LOCATION:Room 1.38 (Ground Floor\, Turing)
SUMMARY:Scikit-learn's Metadata Routing API - Stefanie Senger
URL:https://pretalx.com/euroscipy-2026/talk/VXRSM8/
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