Statistical learning and modelling
This course will attempt to give an intermediate-level overview of concepts and methods in statistics and statistical modelling. I'll aim to present both mathematical theory including proofs as well as practical details of implementation via description of algorithms and programming.
讲师
Max Menzies
日期
2023年09月19日 至 12月14日
位置
| Weekday | Time | Venue | Online | ID | Password |
|---|---|---|---|---|---|
| 周二,周四 | 10:40 - 12:15 | Online | ZOOM 08 | 787 662 9899 | BIMSA |
修课要求
Strictly speaking, no prerequisite is necessary other than basic linear algebra and real analysis, but the following could be helpful for motivation: an understanding of measure theory; an introductory course in statistics, covering concepts such as sampling, the normal distribution, etc; an introductory course in statistical learning covering things like linear regression.
课程大纲
Larry Wasserman, All of Statistics: A Concise Course in Statistical Inference
Gareth James et al, An Introduction to Statistical Learning
Trevor Hastie et al, The Elements of Statistical Learning
Gareth James et al, An Introduction to Statistical Learning
Trevor Hastie et al, The Elements of Statistical Learning
听众
Graduate
视频公开
公开
笔记公开
公开
语言
英文