Mathematics Colloquia and Seminars

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Data has shape, and shape matters. In this talk, I will define persistent homology and show how it can be used to discern topological features (e.g. number of connected components, holes, voids) of data and how these features can be used to extract information about the data. No background is needed for this talk, but a little bit of algebra and topology will be useful.