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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
Analysis II
14
Analysis III
15
Unsupervised Learning
16
The End
Resources
Acknowledgments
14
Analysis III
Start:
Monday, April 26
End:
Friday, April 30
14.1
Summary
Coming soon!
14.2
Learning Objectives
Coming soon!
14.3
Reading
Coming soon!
14.4
Video
Coming soon!
14.5
Assignments
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14.6
Office Hours
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14.7
Additional Information
Coming soon!
13
Analysis II
15
Unsupervised Learning
On this page
14
Analysis III
14.1
Summary
14.2
Learning Objectives
14.3
Reading
14.4
Video
14.5
Assignments
14.6
Office Hours
14.7
Additional Information