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Universes as Bigdata- From Geometry, to Physics, to Machine-Learning

Offered By: Applied Algebraic Topology Network via YouTube

Tags

Theoretical Physics Courses Artificial Intelligence Courses Data Science Courses Machine Learning Courses Combinatorics Courses Differential Geometry Courses Representation Theory Courses Computational Geometry Courses Algebraic Geometry Courses

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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