Henry Adams - Topology in Machine Learning
Offered By: Applied Algebraic Topology Network via YouTube
Course Description
Overview
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.
Syllabus
Henry Adams (5/3/22): Topology in Machine Learning
Taught by
Applied Algebraic Topology Network
Related Courses
Social Network AnalysisUniversity of Michigan via Coursera Intro to Algorithms
Udacity Data Analysis
Johns Hopkins University via Coursera Computing for Data Analysis
Johns Hopkins University via Coursera Health in Numbers: Quantitative Methods in Clinical & Public Health Research
Harvard University via edX