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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 I
14
Analysis II
15
Unsupervised Learning
16
The End
Resources
Acknowledgments
14
Analysis II
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 I
15
Unsupervised Learning
On this page
14
Analysis II
14.1
Summary
14.2
Learning Objectives
14.3
Reading
14.4
Video
14.5
Assignments
14.6
Office Hours
14.7
Additional Information