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STAT 432
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Table of contents
Basics of Statistical Learning
Syllabus
1
Overview
2
Linear Regression
3
Nonparametric Regression
4
Classification Introduction
5
Exam I
6
Binary Classification
7
Generative Models
8
Resampling
9
Regularization
10
Exam II
11
Break
12
Ensemble Methods
13
ML in Practice I
14
ML in Practice II
15
Reading Week
16
The End
Analyses
16
The End
Start:
Monday, May 10
End:
Friday, May 14
16.1
Summary
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16.2
Learning Objectives
Coming soon!
16.3
Reading
Coming soon!
16.4
Video
Coming soon!
16.5
Assignments
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16.6
Office Hours
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16.7
Additional Information
Coming soon!
15
Reading Week
Analyses
On this page
16
The End
16.1
Summary
16.2
Learning Objectives
16.3
Reading
16.4
Video
16.5
Assignments
16.6
Office Hours
16.7
Additional Information