ADTA 5560 - Recurrent Neural Networks for Sequence Data

Fundamentals and practical implementations of Recurrent Neural Networks, focusing on Long Short-Term Memory (LSTM) networks. Emphasis on applying current AI frameworks to build artificial neural networks for deep learning solutions to problems in business, industry, and science. The course provides the student with a guide through how to use TensorFlow and Keras, the two most popular AI frameworks at present, to build artificial neural networks for deep learning that will be trained on the sequence data of which time series is one example. This course covers both the theory and the practical implementation of the AI network. As the fundamentals are discussed, exemplary AI techniques will be employed to illustrate how AI deep learning theories can be applied to real-world solutions using various programming and system tools.

Prerequisite(s): One of the courses: ADTA 5240 , ADTA 5250 , ADTA 5340 , or ADTA 5550 , or the instructor consent.