The course provides an introduction to basic neural network architectures and their applications. Students learn to construct neural networks and train them to solve engineering problems, specifically pattern recognition and function approximation. Mathematical analysis of network architectures, training algorithms and practical applications of neural nets. (Co-listed with Sys Eng 5212)
Time/Day: 04:00 PM - 06:30 PM TR
Prerequisites: Graduate Standing.
Course Component(s): Lecture
For live class lectures, you will log in using the Zoom UM System link in Canvas. For accessing class recordings, you will need to contact your instructor directly.
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