EC ENGR C147

Neural Networks and Deep Learning

Description: 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.

Units: 4.0
1 of 1
1 of 1

Adblock Detected

Bruinwalk is an entirely Daily Bruin-run service brought to you for free. We hate annoying ads just as much as you do, but they help keep our lights on. We promise to keep our ads as relevant for you as possible, so please consider disabling your ad-blocking software while using this site.

Thank you for supporting us!