Statistics 797N - ST-NonParametericRegress/Data

Fall
2018
01
3.00
John Staudenmayer
M W F 1:25PM 2:15PM
UMass Amherst
81910
Lederle Grad Res Tower Rm 145
jstauden@math.umass.edu
Non-parametric regression techniques and concepts such as splines, kernels, regularization, and cross-valdiation are both important for the development and understanding of modern machine / statistical learning and also extremely useful and flexible tools for data analysis. Students in this course will learn how to use non-parametric techniques to analyze data and how the methods work. The course will focus on practical methods for data analysis not theory.
Open to Graduate students only. STATISTC 607, 608, & 625 Prerequisites: Stat 607/608, Stat 625, or permission of the instructor
Permission is required for interchange registration during the add/drop period only.
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