| Relevance of Course Objectives and Core Learning Outcomes(%) |
Teaching and Assessment Methods for Course Objectives |
| Course Objectives |
Competency Indicators |
Ratio(%) |
Teaching Methods |
Assessment Methods |
| 矩陣計算是研讀AI、數據科學的基本工具︒本課程是研讀矩陣計算的入門，除了數據模擬的基本概念外，本課程能提供學生實用性的知識，當與實務數據結合使用時，可以解決實際的問題︒ |
|
|
| topic Discussion/Production |
| Exercises |
| Discussion |
| Lecturing |
|
| Written Presentation |
| Attendance |
| Assignment |
|
| Course Content and Homework/Schedule/Tests Schedule |
| Week |
Course Content |
| Week 1 |
矩陣理論分析 |
| Week 2 |
矩陣理論分析 |
| Week 3 |
SVD處理影像作壓縮 |
| Week 4 |
矩陣正交性應用：最佳化計算 |
| Week 5 |
矩陣正交性應用：最佳化計算 |
| Week 6 |
矩陣正交性應用：最佳化計算 |
| Week 7 |
Tensor Decomposition |
| Week 8 |
Tensor Decomposition |
| Week 9 |
期中作業報告 |
| Week 10 |
Clustering and NMF |
| Week 11 |
Clustering and NMF |
| Week 12 |
Classification of Handwritten Digits |
| Week 13 |
Classification of Handwritten Digits |
| Week 14 |
Text Mining |
| Week 15 |
PCA & MDS |
| Week 16 |
PCA & MDS
期末報告與複習
期末報告與複習 |
self-directed
learning |
|
|
| Evaluation |
期中報告(50%)
期末報告(50%) |
| Textbook & other References |
1. Lars Elden, Matrix Methods in Data Mining and Pattern Recognition, SIAM 2007.
2. Golub & Von Loan, Matrix Computations, 3rd Ed. , John Hopkins University, 1996.
3. Yuan Yao, A Mathematical Introduction to Data Science, Bejing University, 2014 |
| Teaching Aids & Teacher's Website |
|
| Office Hours |
| 週一 10:00-12:00 (預約） |
| Sustainable Development Goals, SDGs(Link URL) |
| | include experience courses：N |
|