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SUMMARY:Elizabeth Munch (Michigan State University)
DTSTART:20230315T140000Z
DTEND:20230315T153000Z
DTSTAMP:20260423T024518Z
UID:bM2L/2
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/bM2L/2/">Cra
 fting Topological Features for Machine Learning Pipelines</a>\nby Elizabet
 h Munch (Michigan State University) as part of Barcelona Mathematics and M
 achine Learning Colloquium Series\n\n\nAbstract\nThe field of topological 
 data analysis (TDA) has exploded in the last twenty years. This suite of t
 ools creates methods for quantifying shape in data by incorporating ideas 
 from a wide range of subjects such as topology\, geometry\, algebra\, cate
 gory theory\, and graph theory. In this talk we will discuss the basic set
 up of some of main tools in TDA\, how these can be fit into an ML pipeline
 \, and show example applications highlighting the kinds of structures that
  can be found with these methods.\n
LOCATION:https://researchseminars.org/talk/bM2L/2/
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