Units:4 Introduction to machine learning with an emphasis on the underlying mathematics. Topics such as VC dimension, central limit theorem, gradient descent. Applications such as SVM and neural nets.
Prerequisites: MATH 230 and MATH 310; or M.S. Computer Science major. Possible Instructional Methods:Entirely On-ground. Grading: A-F grading only. Cross-listed: MATH 667.
