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UID:pretalx-pydata-amsterdam2026-GDUDY8@pretalx.com
DTSTART;TZID=CET:20260910T111500
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DESCRIPTION:In a time where important tasks and decisions are handled by la
 rge and opaque AI models\, **it’s easy to lose touch** with the algorith
 ms behind them. Do we still recognise the building blocks? **Can we still 
 reason about how models work?**\nThis talk invites you into a time machine
  to **rediscover** algorithms you may have missed or forgotten about. By s
 eeing the beauty and imperfections of past technological solutions\, we ho
 pe to gain a clearer view on evaluating models in the current age.\n\nDraw
 ing from over a decade of academic and industry experience\, four **20th-c
 entury classical Machine Learning** families are presented based on real-l
 ife use cases. With a minimum of formulas and technical details\, we’ll 
 see what made the ideas behind them so compelling\, what we can learn from
  them\, and if they are still relevant today.\nThe format of the presentat
 ion is largely conceptual and with an emphasis on distilling **applicable 
 insights**.\n\nWho needs to attend this? It’s primarily for data scienti
 sts (practitioners and researchers at all levels)\, but really also **for 
 everyone interested in the history and philosophy of AI**. Basic knowledge
  about machine learning is beneficial.\nBest available **Python implementa
 tions** of the discussed methods are provided. Code with working examples 
 will be shared in a Github repo.\n\nYou will leave this talk with a **rich
 er appreciation of classical ML**\, with valuable modelling insights\, and
  you’ll have what’s needed to try your hand at a few funky classics yo
 urself.
DTSTAMP:20260710T150510Z
LOCATION:Room 1 (170)
SUMMARY:A short tour of forgotten Machine Learning algorithms - Christiaan 
 Erdbrink
URL:https://pretalx.com/pydata-amsterdam2026/talk/GDUDY8/
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