ACS 3520 Deep Learning (DS 2.2)
This course provides an introduction to deep learning. Students will learn a series of neural network architectures including the perceptron, fully connected deep neural networks and convolutional neural networks. Students will construct their own simple feed-forward neural network from scratch and learn to train it via backpropagation using gradient descent. The course will cover the use of industry standard libraries to create and fine-tune sophisticated neural network models, and to build end-to-end data processing pipelines to train the models. Prerequisites: ASC 2511 (DS 1.11)