Course Detail
Units:
3.0
Course Components:
Lecture
Enrollment Information
Enrollment Requirement:
Prerequisites: 'C-' or better in (CS3500) AND 'C' or better in ((MATH1311 AND 1321) OR MATH2210) AND Foundational Courses complete AND (Major OR Minor in Kahlert School of Computing OR ECE)
Description
Foundations and details of deep learning, with implementations and applications. Students learn to implement, train and debug their own neural networks and gain a detailed understanding of cutting-edge research in machine learning applications, such as computer vision and natural language processing. Covers learning algorithms, neural network architectures, validation/evaluation of performance, and practical engineering tricks for training and fine-tuning networks for tasks such as object recognition and language translation.