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
13
Analysis II
Start:
Monday, April 19
End:
Friday, April 23
13.1
Summary
Coming soon!
13.2
Learning Objectives
Coming soon!
13.3
Reading
Coming soon!
13.4
Video
Coming soon!
13.5
Assignments
Coming soon!
13.6
Office Hours
Coming soon!
13.7
Additional Information
Coming soon!
12
Analysis I
14
Analysis III
On this page
13
Analysis II
13.1
Summary
13.2
Learning Objectives
13.3
Reading
13.4
Video
13.5
Assignments
13.6
Office Hours
13.7
Additional Information