Deep Learning

Catalog description

Deep learning represents a set of emerging techniques in machine learning that has quickly become prevalent in the analysis of big data. The power and potential of this recent breakthrough in intelligent computer systems has been demonstrated through many successes. Deep learning systems are the current best performer in computer vision and speech processing. A wide variety of active researches are being conducted to leverage the capability of deep learning for achieving automation in areas such as autonomous driving, robotics, and automated medical diagnosis. There is a crucial need to educate our students on such new tools. This course gives an in-depth coverage of the advanced theories and methods in deep learning including basic feedforward neural networks, convolutional neural networks, recurrent neural networks including long short-term memory models, deep belief nets, and autoencoders. It will make an emphasis on approaches with practical relevance, and discusses a number of recent applications of deep networks applications in computer vision, natural language processing and reinforcement learning.