CS 752 (H01) - Foundations of Neural Networks

Foundtns ofNeural Networks\Hon

Durham   Engineering&Physical Sciences :: Computer Science
Credits: 4.0
Term: Fall 2024 - Full Term (08/26/2024 - 12/09/2024)
Grade Mode: Letter Grading
CRN: 16759
Neural networks are a class of machine learning models which have recently revolutionized many applied machine learning domains such as natural language understanding, image/video processing, bioinformatics, time series analysis. This course teaches students to develop new neural network architectures from scratch and customize them. The course covers all necessary foundations of neural networks including gradient descent optimization and vector calculus. Students will learn how to design models using idioms such as observed variables, latent variables, gate variables and different functions as well as a wide range of state-of-the-art architectures as design examples.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Prerequisite(s): CS 515
Cross listed with : CS 752.01, CS 852.01
Attributes: Honors course
Instructors: Laura Dietz

Times & Locations

Start Date End Date Days Time Location
8/26/2024 12/9/2024 MW 3:40pm - 5:00pm KING N101
8/26/2024 12/9/2024 M 5:10pm - 6:00pm KING N328