Henry Adams - Topology in Machine Learning

Explore the intersection of topology and machine learning in this illuminating lecture from the Applied Algebraic Topology Network. Delve into the concept of "vectorizing" geometry and its application as a feature in machine learning, with a focus on persistent homology. Discover how this technique is utilized in various fields, including materials science, computer vision, and agent-based modeling. Gain insights into the relationship between these methods and the local geometry of datasets, as well as their connection to explainable machine learning. Learn from examples involving flocks of birds and schools of fish to understand the practical applications of topological data analysis in complex systems.