Skip to main content
STAT 432
Show table of contents
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
Ensemble Methods
12
Analysis I
13
Analysis II
14
Analysis III
15
Unsupervised Learning
16
The End
Resources
Acknowledgments
16
The End
Start:
Monday, May 10
End:
Friday, May 14
16.1
Summary
Coming soon!
16.2
Learning Objectives
Coming soon!
16.3
Reading
Coming soon!
16.4
Video
Coming soon!
16.5
Assignments
Coming soon!
16.6
Office Hours
Coming soon!
16.7
Additional Information
Coming soon!
15
Unsupervised Learning
Resources
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