CSC 426 Deep Learning (3 credits)

Hours: 3 classroom + 0 lab/studio
Prerequisite(s): C- or better in MAT 227 and CSC 364 and junior standing or higher
Taught: Spring only-even years
An introduction to neural networks and deep learning covering concepts and theories of multi-layer neural networks, back-propagation, stochastic gradient descent, convolutional neural networks, recurrent neural networks and other deep learning-based algorithms. Students will apply what they learn to building neural networks using Python and TensorFlow
Repeatable: No
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