| Relevance of Course Objectives and Core Learning Outcomes(%) |
Teaching and Assessment Methods for Course Objectives |
| Course Objectives |
Competency Indicators |
Ratio(%) |
Teaching Methods |
Assessment Methods |
| 了解如何使用機器學習進行統計資料分析 |
| 1.Statistical Thinking and Logic |
| 2.Data Analysis, Statistical Modeling and Software Application |
| 3.Statistical Computing and Simulation Study |
| 4.Professional Knowledge and Literature Review |
|
|
| topic Discussion / Production |
| Networking / Distance Education |
| Discussion |
| Other |
| Lecturing |
|
| Written Presentation |
| Attendance |
| Oral Presentation |
| Assignment |
| Quiz |
| Internship |
| Other |
|
| Course Content and Homework/Schedule/Tests Schedule |
| Week |
Course Content |
| Week 1 |
Introduction |
| Week 2 |
Regression |
| Week 3 |
Regression (Classification) |
| Week 4 |
SVM |
| Week 5 |
Decision Tree |
| Week 6 |
Ensamble Learning |
| Week 7 |
PCA |
| Week 8 |
Mid-term exam or report |
| Week 9 |
Clustering |
| Week 10 |
DNN I |
| Week 11 |
DNN 2 |
| Week 12 |
CNN |
| Week 13 |
RNN |
| Week 14 |
AE |
| Week 15 |
GAN |
| Week 16 |
Final exam or report |
self-directed
learning |
03.Preparing presentations or reports related to industry and academia.
|
|
| Evaluation |
小考/出席率（～60%）：補考成績*60%
學習筆記/作業（～20%）
大考/報告（～10%）
其他（～10%）
平常請自行確認成績/學期結束後不開放查詢
總成績會做調整/最高96分/無補救方式 |
| Textbook & other References |
| 2019_Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition by Aurélien Géron (z-lib.org) |
| Teaching Aids & Teacher's Website |
| https://www.youtube.com/channel/UCSivAooQ-OTLATS1dTT3DZw |
| Office Hours |
| 預約 |
| Sustainable Development Goals, SDGs(Link URL) |
| include experience courses：N |
|