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SUMMARY:Janusz Przewocki
DTSTART:20260420T103000Z
DTEND:20260420T123000Z
DTSTAMP:20260423T041113Z
UID:BNAT/22
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/BNAT/22/">Un
 supervised Learning (Part 1)</a>\nby Janusz Przewocki as part of Basic Not
 ions and Applied Topology Seminar\n\nLecture held in Room 1 at the IMPAS\,
  Room 1.14 at the Institute of Informatics (University of Gdańsk).\n\nAbs
 tract\nThis first session introduces the motivations and foundational meth
 ods for dimensionality reduction under unsupervised learning. We begin by 
 discussing why dimension reduction matters - especially in high-dimensiona
 l data settings - and how it helps address issues like the "curse of dimen
 sionality\," multicollinearity\, overfitting\, and challenges in visualiza
 tion and interpretation. Then we focus on Principal Component Analysis (PC
 A): its mathematical foundations\, how it identifies dominant modes of var
 iation\, how to interpret the principal components\, and how to choose the
  number of components.\n
LOCATION:https://researchseminars.org/talk/BNAT/22/
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