Oct 05, 2022  
2022-23 Catalog 
    
2022-23 Catalog
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ECE 6230 - Engineering Applications in Deep Learning

Credits: (3)
Typically Taught Spring Semester: Full Sem
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.
Pre-requisite(s): ECE 1400 , ECE 3210 , MATH 3410 , and either MATH 2250  or MATH 2270 .



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