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UID:pretalx-juliacon-2026-VXYAQY@pretalx.com
DTSTART;TZID=CET:20260813T123000
DTEND;TZID=CET:20260813T124500
DESCRIPTION:Symbolic learning is a branch of machine learning focused on bu
 ilding classifiers that can be translated into logical rules\, making them
  far more readable than neural networks or other statistical models. While
  training a symbolic model is a necessary first step\, it is the post-proc
 essing stage that yields the most relevant insights. We present a live wal
 kthrough of SolePostHoc.jl\, a SOLE package dedicated to post-processing\,
  allowing for rule extraction\, boosting and model simplification.
DTSTAMP:20260502T104017Z
LOCATION:Room 2
SUMMARY:Symbolic post-hoc analysis with SolePostHoc.jl - Marco Perrotta
URL:https://pretalx.com/juliacon-2026/talk/VXYAQY/
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