CSCI 6379 Deep Learning
In this course, the theory and practice of neural computation for machine learning are introduced. Starting with feed forward neural networks, more complicated multi-layered "deep" networks are then covered, including basic back-propagation, gradient descent and modern regularization techniques. The class will look at modern deep learning techniques: convolutional neural networks, deep belief networks and deep recurrent neural models. The course also provides acquaintance with some of the software libraries available for building and training deep neural networks.