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UID:pretalx-pyconde-pydata-2024-BFF9VA@pretalx.com
DTSTART;TZID=CET:20240422T161000
DTEND;TZID=CET:20240422T165500
DESCRIPTION:I know you probably don't want to hear about it\, but your deep
  learning model probably memorized some of its training data. In this talk
 \, we'll review active research on deep learning and memorization\, partic
 ularly for large models such as large language and multi-modal models.\n\n
 We'll also explore potential ways to think through when this memorization 
 is actually desired (and why) as well as threat vectors and legal risk of 
 using models who have memorized training data. We'll also look at potentia
 l privacy protections which could address some of the issues and how to em
 brace memorization by thinking through different types of models and their
  use.
DTSTAMP:20260415T093651Z
LOCATION:B07-B08
SUMMARY:Your Model _Probably_ Memorized the Training Data - Katharine Jarmu
 l
URL:https://pretalx.com/pyconde-pydata-2024/talk/BFF9VA/
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UID:pretalx-pyconde-pydata-2024-BFYUUJ@pretalx.com
DTSTART;TZID=CET:20240424T131000
DTEND;TZID=CET:20240424T141000
DESCRIPTION:For the third year in a role\, the PyLadies Panel at PyCon PyDa
 ta engages with a broader audience on critical issues related to gender di
 sparities\, ethics\, and the ongoing importance of women-focused tech grou
 ps. Adopting unconventional formats\, the PyLadies Panel aims to foster me
 aningful discussions among PyLadies members and the Python community\, enc
 ouraging open dialogue and community solidarity.
DTSTAMP:20260415T093651Z
LOCATION:Kuppelsaal
SUMMARY:(PyLadies Panel) Reflecting Within: Challenging Narratives in Tech 
 Feminism - Cheuk Ting Ho\, Katharine Jarmul\, Paloma Oliveira\, Naa Ashior
 kor Nortey
URL:https://pretalx.com/pyconde-pydata-2024/talk/BFYUUJ/
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