EC ENGR C147A
Neural Networks and Deep Learning
Electrical and Computer Engineering · 4 units · Undergraduate upper division (100-199)
(Formerly numbered C147.) 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 C247A.
Letter grading.
Requisites
Official UCLA wording
Recommended requisites: courses 131A, 133A or 205A, and M146, or equivalent.
BruinTree reads · Recommended
needs reviewconfidence 0.25 · from text- all of
- equivalent
- · could not read "equivalent" (no course number found)
- · mixed comma-level AND/OR in "courses 131A, 133A or 205A, and M146, or equivalent" — grouping is a best reading
Requires
Everything that has to come before this course, not just the courses named in the requisite above.
EC ENGR C147A
- EC ENGR 131AProbability and Statistics
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
EC ENGR C147A
- EC ENGR C147BNeural Networks and Deep Learning II
- EC ENGR 201CArtificial Intelligence on Chip
2 courses list this as a requisite. The whole downstream is here — 2 courses over 1 level. Every course here opens its own tree.