Universes as Bigdata- From Geometry, to Physics, to Machine-Learning
Offered By: Applied Algebraic Topology Network via YouTube
Course Description
Overview
Explore the fascinating intersection of string theory, algebraic geometry, and machine learning in this 58-minute lecture by Yang-Hui He. Trace the historical evolution of theoretical physics from its roots in geometry to its current applications in data science. Delve into the Calabi-Yau landscape, a collaborative effort spanning four decades across physics, mathematics, and computer science. Discover how artificial intelligence is revolutionizing mathematical research, with applications ranging from geometry and representation theory to combinatorics and number theory. Gain insights into the cutting-edge program of machine-learning mathematical structures and contemplate the profound impact of AI on the future of mathematical discovery.
Syllabus
Yang-Hui He (6/16/21): Universes as Bigdata: from Geometry, to Physics, to Machine-Learning
Taught by
Applied Algebraic Topology Network
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