Statistical learning and modelling II
This course will follow from the previous course last semester. We will finish the statistical theory in Wasserman and then turn to additional theory in ESL and the Python labs in ISL.
Lecturer
Matthew Cedric Menzies
Date
8th March ~ 3rd June, 2024
Location
| Weekday | Time | Venue | Online | ID | Password |
|---|---|---|---|---|---|
| Friday | 15:00 - 19:00 | Online | ZOOM 05 | 293 812 9202 | BIMSA |
Prerequisite
The previous course, or a broad theoretical basis in statistics.
Reference
Larry Wasserman, All of Statistics
Larry Wasserman, All of Nonparametric Statistics
James et al, Introduction to Statistical Learning
Hastie et al, Elements of Statistical Learning
Larry Wasserman, All of Nonparametric Statistics
James et al, Introduction to Statistical Learning
Hastie et al, Elements of Statistical Learning
Audience
Graduate
Video Public
Yes
Notes Public
Yes
Language
English