ECE 6230 - Eng Apps in Deep Learning

Institution:

Weber State University

Subject:

Description:

This course covers deep learning architectures with a focus on learning end-to-end models for these tasks, particularly image and signal processing. Students will learn to implement, train and debug their own deep neural networks and gain a detailed understanding of cutting-edge research in this field. Strong emphasis will be placed on real-world applications for both solving engineering problems using these methods as well as practical techniques for training and fine-tuning the networks. Case studies will be drawn from medical imaging, semiconductors, and audio signal processing.

Credits:

3.00

Credit Hours:

Prerequisites:

ECE 3210 and ECE 3430 and ENGR 2240 and MATH 2250 and MATH 2270 and MATH 3410

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.weber.edu

Phone Number:

(801) 626-6000

Regional Accreditation:

Northwest Commission on Colleges and Universities

Calendar System:

Semester

General Education

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