EPPS6326 - Machine Learning for Socio-Economic and Geo-Referenced Data

EPPS 6326 (GISC 6323) Machine Learning for Socio-Economic and Geo-Referenced Data (3 semester credit hours) Models and algorithms as well as their underlying conceptional foundations to structure dynamic socio-economic and geo-referenced data are introduced. Open-source software and commonly available hardware are used. Practical examples of [a] supervised machine learning to develop classification rules and [b] unsupervised data mining to uncover a hidden organization of data objects are used to explore the strength and weaknesses of selected data analytical methods and to examine the resulting output. Where appropriate, ethical ramifications are discussed. (3-0) T