Course Code |
STAT 4001 STAT4001 |
科目名稱 |
Data Mining & Stat Learning 數據挖掘及統計學習 |
||||||||
教員 |
學 分 |
||||||||||
課程性質 |
STAT選修 (Data Analytics Stream必修) |
同科其他選擇 |
|
||||||||
Workload |
l 非PAPER類HOMEWORK l MIDTERM l FINAL EXAM |
好重 |
|
||||||||
重 |
|
||||||||||
平均 |
|
||||||||||
輕 |
1 |
||||||||||
極輕 |
|
||||||||||
評價教學內容 |
#1教好多Statistical Learning嘅algorithm, Tutorial全部都係R examples,
Homework偏難且冇答案, 建議R底差嘅同學唔好讀 |
||||||||||
評價教員教學 |
#1講嘢好悶 |
||||||||||
CUSIS科目資料 |
Description: This course
covers the principles of data mining, exploratory analysis and visualization,
as well as predictive modeling for complex data sets. It introduces modern
tools for regression and classification for high-dimensional or ultra-high
dimensional data from the perspective of statistical decision theory and
makes comparison to traditional methods. Students are exposed to statistical
principles, computational issues, and hands-on data analysis on high noise,
observational data. Learning
Outcome: Upon completion
of the course, students should be able to
(1) use various
statistical methods and techniques to summarize and present high-dimensional
data; (2) build
predictive models for complex data sets;
(3) master the
concepts of regularization, model selection, model averaging and ensemble
learning; and (4) write R
code and use R packages to solve real-world problems. |
||||||||||
其他資料 |
2021Sem1:學位 87|註冊 83|剩餘 4 |
||||||||||
同學推薦 |
高度推薦 |
|
推薦 |
|
有保留 |
1 |
極有保留 |
|
沒有留言:
發佈留言