Course Description
Techniques for the design of neural networks for machine learning. An introduction to deep learning. Emphasis on theoretical and practical aspects including implementations using state-of-the-art software libraries. Requirement: Programming experience (an object-oriented language such as Python), linear algebra (MA 405 or equivalent), and basic probability and statistics.
Spring 2025
Instructors
Meeting Patterns
Classes Start:
January 6, 2025
Classes End:
April 22, 2025
Location:
01103 James B Hunt Jr Centenni
Class Days:
T H
Class Start Time:
3:00pm
Class End Time:
4:15pm
Class Type:
Lecture
Credits:
3.00
Restrictions:
Prerequisite: ECE graduate students and ECE undergrads with a 3.5 or higher GPA
