Lecture, four hours; discussion, two hours; outside study, six hours. 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 C147. Letter grading.

Review Summary

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Enrollment Progress

Dec 2, 3 PM PST
LEC 80: 26/35 seats taken (Open)
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Section List

  • LEC 80

    Open (4 seats)

    Varies ---

    Online - Asynchronous

Course

Previously taught
24W

Previous Grades

Grade distributions not available.