Capstone: Applying Machine Learning and Neural Networks

Catalog description

This Graduate course provides students with an overview of appropriate theories and models that are used to represent neural networks. Students will gain foundational knowledge in developing constructs to evaluate and represent components associated with neural networks and learning algorithms. Topics for this course include propagation, feedforward networks, perceptrons, and self-organizing networks. Prerequisite: CSC510.