MATH 8335 Deep Learning
This course is concerned with advanced concepts of Deep Learning. Topics include but are not limited to: multilayer perceptron and artificial neural networks, computer vision architectures, convolutional neural network architectures, sequential modeling, recurrent neural networks, LSTM, natural language processing, and other selected topics like Bayesian neural networks, autoencoder neural networks, universal approximation theory, and hyperparameter optimization as well as applications in healthcare and engineering.
Prerequisite
Consent of instructor.
Offered
As scheduled