| 週次 |
授課內容 |
| 第1週 |
Introduction to Data Mining and Data Preprocessing |
| 第2週 |
Mining Frequent Patterns and Associations: Basic of Association Rule |
| 第3週 |
Mining Frequent Patterns and Associations: Apriori and FP-Tree |
| 第4週 |
Classification: Decision Tree and Bayes Classification |
| 第5週 |
Classification: K-NN and SVM |
| 第6週 |
Classification: Evaluation / Project Proposal |
| 第7週 |
Clustering: K-Means and Hierarchical Clustering |
| 第8週 |
Midterm Exam |
| 第9週 |
Clustering: Density-based Methods and Model-based Methods |
| 第10週 |
Outlier Detection / Dimension Reduction |
| 第11週 |
Python Tools for Data Mining |
| 第12週 |
Advanced Topic: Recommendation |
| 第13週 |
Advanced Topic: Deep Learning |
| 第14週 |
Advanced Topic: Text Mining and Large Language Model |
| 第15週 |
Final Exam |
| 第16週 |
Project Presentation |
自主學習
內容 |
02.閱覽產業及學術相關多媒體資料
03.製作專題報告
|