本課程主要是針對統計系及資工系開課，也歡迎管理學院修習過統計學課程的學生選修。透過課程講授、個人作業與分組期末報告，在學期末時，修課學生應該具備下面的觀念與技能： (1) 了解什麼資料用什麼方法。 (2) 瞭解資料分析與探勘的過程與步驟方法。 (3) 使用R或Python軟體進行程式撰寫與統計分析。 (4) 視覺化資料進行溝通。 (5) 針對一個有趣或產業的問題，運用教授的統計學習與R、Python語言，進行真實資料的分析。This course is mainly offered to the Department of Statistics and the Department of Finance and Economics. Students who have taken statistics courses in the School of Management are also welcome to take it as an elective. Through course lectures, individual assignments and group final reports, by the end of the semester, students taking the course should have the following concepts and skills: (1) Understand what materials to use and what methods to use. (2) Understand the process and steps of data analysis and exploration. (3) Use R or Python software for program writing and statistical analysis. (4) Communicate through visual information. (5) Aiming at an interesting or industrial problem, use the professor’s statistical learning and R and Python languages to analyze real data.
1.Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani, An Introduction to Statistical Learning with Applications in R.
2.Trevor Hastie, Robert Tibshirani and Jerome Friedman, The Elements of Statistical Learning, Data Mining, Inference, and Prediction. Second Edition.
3.R語言機器學習。吳金朝 譯。
1.Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani, An Introduction to Statistical Learning with Applications in R.
2.Trevor Hastie, Robert Tibshirani and Jerome Friedman, The Elements of Statistical Learning, Data Mining, Inference, and Prediction. Second Edition.
3.R language machine learning. Translated by Wu Jinchao.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 期中考期中考 midterm exam |
30 | |
| 期末報告期末報告 Final report |
30 | |
| 作業作業 Homework |
30 | |
| 平時表現和出席平時表現和出席 Daily performance and attendance |
10 |
