Machine Learning Seminar Series

Location: RI 215

Speaker: Affan Shoukat, University of Regina

Title: What is a neural network?

Abstract:

In this first talk, I will provide an overview of artificial neural networks to lay the foundation for future sessions. Neural networks are function approximators that learn patterns from data, enabling them to perform tasks such as classification, regression, and prediction. They are widely used in machine learning for solving complex problems in fields like image recognition, natural language processing, and scientific modeling.  Their ability to model non-linear relationships and capture intricate patterns in large datasets has made them essential tools in modern data analysis and predictive modeling. This session will be followed by a proof of the universal approximation theorem for neural networks, so you won't want to miss this.