On the Applications of Topology

Explore the applications of topology in data analysis through this mathematics department colloquium talk by Sara Kalisnik from ETH. Delve into the adaptation of topological techniques for studying large and complex datasets, focusing on two prominent methods: persistent homology and mapper. Discover how these topological approaches are applied in various fields such as computer vision, biology, and medicine. Learn about the integration of topological methods with traditional machine learning techniques, gaining insights into the interdisciplinary nature of modern data analysis. Enhance your understanding of how mathematical concepts from topology are transforming the landscape of data science and contributing to advancements across multiple scientific domains.