資料探勘
Data Mining
| 節 | 週四 |
|---|---|
5 13:20–14:10 | 資料探勘 ED301 3 節連堂 |
6 14:20–15:10 | |
7 15:30–16:20 |
* 根據陽明交大上課時間表所列
This course introduces the basic principles and modern techniques of data mining, covering real-world applications and implementation techniques. Paper discussions and project implementation are also included to help build foundational knowledge.
Machine Learning, Artificial Intelligence, Data Structure, Python Programming
The course is mainly taught using lecture slides, with assignments and a project for hands-on practice. Students will also read and present research papers to better understand model design thinking.
3 assignments、1 group project、2 paper presentation/discussion Assignments：40% Group Project：35% Paper Presentation/Discussion：25% (No exam)
- Data Mining Overview
- Data Preprocessing & Model Evaluation
- Association Rules & Frequent Patterns
- Supervised Learning
- Unsupervised Learning
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction to This Course |
| 第 2 週 | Data Preprocessing |
| 第 3 週 | Pattern Mining |
| 第 4 週 | Supervised Learning (1/2) |
| 第 5 週 | Supervised Learning (2/2) |
| 第 6 週 | No Class (Intercollegiate activities) |
| 第 7 週 | Unsupervised Learning (1/2) |
| 第 8 週 | Unsupervised Learning (2/2) |
| 第 9 週 | Semi-Supervised Learning |
| 第 10 週 | Paper Presentation |
| 第 11 週 | Paper Presentation |
| 第 12 週 | Fundamentals of Reinforcement Learning |
| 第 13 週 | Recommender System |
| 第 14 週 | Time Series Analysis |
| 第 15 週 | Data Mining with Large Language Models |
| 第 16 週 | Project Presentation |
1. Jiawei Han, Jian Pei, and Hanghang Tong. Data Mining: Concepts and Techniques, 4th Edition. Morgan Kaufmann Publishers 2023. 2. Pang-Ning Tan, Michael Steinbach, and Vipin Kumar. Introduction to data mining. Pearson Education India, 2016.
- 時間
- by appointment
- 聯絡方式
- by e-mail: lpyting@nycu.edu.tw