Statistical Decision Making and Machine Learning Theory

3 Credits

To teach the statistical theory describing the performance of general Machine Learning and Statistical Decision Making approaches. We will not attempt to describe details of specific machine learning algorithms, code those algorithms and test them on real data. Students will learn some needed hypothesis testing theory and estimation theory that is necessary to understand learning theory. Students will learn Probably Approximately Correct learning theory. Credit will not be given for both ECE 314 and ECE 414 . Prerequisites: ECE 108 and ( MATH 231 or MATH 309 )