ECE X82V ECE 382V Topics in Computer Engineering 3 Hours
3 Lecture Hours 0 Lab Hours
Three lecture hours a week for one semester.
Pre/Corequisites: Graduate standing.
Grading: Student Option
Repeatable for credit: May be repeated for credit when the topics vary.
Academic Level: Doctoral
Topic 2: Large-Scale Learning. Examine feedforward neural networks, convolutional neural networks, deep learning training by backpropagation, interpretability of deep neural networks, and prediction and overfitting. Explore statistical Learning theory, unsupervised machine learning, deep generative unsupervised models, and generative adversarial networks and autoencoders. Apply deep learning using Python, Tensorflow and Keras. Electrical and Computer Engineering 382V (Topic 2) and Electrical Engineering 382V (Topic 2) may not both be counted.