Deep Learning and Neural Architectures

3 credits · Graduate School

Advanced neural network architectures and deep learning techniques. Backpropagation, regularization, transfer learning, and model generalization. Design, implementation, and optimization of deep learning models such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory networks (LSTMs), and Transformers. No credit for students who have earned credit for ECE 4609. [3]