Mathematics for Deep Neural Networks: Introduction - Lecture 1 of 5

Explore the foundations of deep neural networks in this comprehensive lecture, part of the TRIAD Distinguished Lecture Series. Delve into the mathematics behind various neural network types, examining their complexity and data processing capabilities. Gain insights into the algorithms used for fitting deep networks to data and survey the key ideas underlying existing mathematical theories. Discover the diverse approaches to understanding deep networks through a mathematical lens, providing a solid foundation for further exploration in the field of artificial intelligence and machine learning.

TRIAD Distinguished Lecture Series | Johannes Schmidt-Hieber Lecture 1 (of 5)