進階資料分析
Advanced Data Analysis with R
| 節 | 週二 |
|---|---|
2 09:00–09:50 | 進階資料分析 MB415（光復） 3 節連堂 |
3 10:10–11:00 | |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
This course will have two parts. In the first part, you will learn how to program in R. In the second part, you will learn how to use R to analyze data.
基本程式設計概念與能力
無備註
1.作業嚴禁抄襲 2.請同學注意E3公告
Quiz: 10% 作業:25% 期中考試:35% Data Science Competition: 30%
Introduction to R Programming
1.Introduction 2.Data Types 3.Programming Structure 4.Function
- 講授：
- 15
- 示範：
- 9
Advanced Data Analysis
1.Visualization 2.Artificial Neural Network 3.Support Vector Machines 4.Tree-based Methods
- 講授：
- 15
- 示範：
- 9
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction |
| 第 2 週 | Vectors and Matrices |
| 第 3 週 | Lists and Data Frames |
| 第 4 週 | Data Reading and Data Frames |
| 第 5 週 | National Holiday |
| 第 6 週 | Factors and Tables |
| 第 7 週 | functions and R Programming Structures |
| 第 8 週 | Data Wrangling |
| 第 9 週 | Visualization |
| 第 10 週 | Midterm Exam |
| 第 11 週 | Visualization |
| 第 12 週 | Introduction to Machine Learning/Linear Regression |
| 第 13 週 | Ridge Regression/Logistic Regression |
| 第 14 週 | Introduction to caret |
| 第 15 週 | kNN/SVM |
| 第 16 週 | xgboost/Ensemble Learning |
| 第 17 週 | Decision Trees/Neural Netowrks |
| 第 18 週 | Data Science Competition Presentation |
1. The Art of R Programming: A Tour of Statistical Software Design by Norman Matloff (Publisher: No Starch Press; 1 edition (October 15, 2011) 2. The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie, Robert Tibshirani and Jerome Friedman. [free download] https://web.stanford.edu/~hastie/ElemStatLearn/ 3. R Cookbook, By Paul Teetor, Publisher: O'Reilly Media
- 地點
- MB 505R
- 時間
- 另行安排
- 聯絡方式
- clliu@mail.nctu.edu.tw