EC ENGR C247A
Neural Networks and Deep Learning
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From the registrar's catalog
(Formerly numbered C247.) Lecture, four hours; discussion, two hours; outside study, six hours. Recommended requisites: courses 131A, 133A or 205A, and M146, or equivalent. Review of machine learning concepts; maximum likelihood; supervised classification; neural network architectures; backpropagation; regularization for training neural networks; optimization for training neural networks; convolutional neural networks; practical CNN architectures; deep learning libraries in Python; recurrent neural networks, backpropagation through time, long short-term memory and gated recurrent units; variational autoencoders; generative adversarial networks; adversarial examples and training. Concurrently scheduled with course C147A. Letter grading.
Sections in Spring 2027
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