Neural Networks and Deep Learning

EC ENGR C247 - Neural Networks and Deep Learning

<p>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 C247. Letter grading.</p>

Electrical and Computer Engineering

Known as the birthplace of the Internet and where countless other cutting-edge technologies took their first steps, the school is consistently ranked among the top 10 public engineering schools in the U.S.

Henry Samueli School of Engineering and Applied Science

Electrical and computer engineering continues to make vital contributions to expand access, processing, and control of the vast amount of information and data in the world.

General Catalog

Neural Networks and Deep Learning

EC ENGR C147

4 units