CSCI 6379 Neural Networks and 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.
Offered
As Scheduled