Applied Machine Learning for Electrical & Computer Engineering

Catalog description

Fundamental concepts, methods, and technologies of machine learning. Design, modelling, implementation, and optimization of hardware architectures for machine learning systems. Machine/deep learning for signal detection, channel modeling, estimation, interference mitigation, and decoding. Performance analysis and evaluation of machine learning techniques in communication and networks systems. Machine learning for emerging communication systems and applications, such as drone systems, IoT, autonomous navigation and robotics, edge computing, smart cities, and vehicular networks. Prerequisites: EECE 304 and EECE 306 . Cross-listed with ECEG 748 .