EE538 Neural Networks, KAIST homework code
Professor: Soo-Young Lee
Textbook: S. Haykin, Neural Networks and Learning Machines (3rd Edition), Prentice Hall, 2008.
This course was designed to provide students capability to create their own deep learning model, i.e., network architectures and learning algorithms, for artificial intelligence based on the brain information processing mechanism. We will discuss neuron models, network architectures, and learning rules. Both unsupervised and supervised learning rules are presented, and both feed-forward and recurrent architectures will be discussed. Also, based on abundant previous works described in the textbook, we will elucidate possible extensions of current deep learning models to new ones.