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Topological Data Science
This lecture explores Topological Data Analysis, a branch of mathematics that deals with the shape of data to provide insights into the underlying structure of knowledge spaces. It delves into understanding the structure of data through mathematical notions in lower dimensions, emphasizing the importance of non-conceptual knowledge systems and the application of Topological Data Analysis. The lecture covers topics such as manifolds, persistent homology, and the comparison of different shapes using mathematical tools. It also discusses the significance of topology in understanding the shape of data and its implications in digital humanities.