資料探勘
Data Mining
學期
114-1
學分
3
學分
當期課號
535702
永久課號
CSDS30009
開課單位
數據科學與工程研究所碩士班
授課教師
顏安孜
校區
光復
類別
選修
上課時間表
| 節 | 週三 |
|---|---|
3 10:10–11:00 | 資料探勘 EC022 2 節連堂 |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
概述
This course is an introductory course on data mining. It briefly introduces the basic concepts, principles, methods, implementation techniques, and applications of data mining. Some advanced techniques in deep learning will also be covered.
先修科目
Machine Learning, Artificial Intelligence, Python Programming
教學方式
上課以投影片內容為主,並指派作業作為實作練習。
評分方式
3 homework、1 term project、1 group presentation Homework:60% Final project:30% Group presentation:10% (No exam)
課程大綱
- Association Analysis
- Regression
- Classification
- Deep Learning for Data Mining
- Introduction to Data Mining
週次計畫
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction of the Course |
| 第 2 週 | Introduction to Data Mining |
| 第 3 週 | Association Analysis |
| 第 4 週 | Regression |
| 第 5 週 | Classification (Basic Concepts and Techniques) |
| 第 6 週 | Neural Networks in Data Mining (DNN) |
| 第 7 週 | Anomaly Detection |
| 第 8 週 | Midterm (No Class) |
| 第 9 週 | Neural Networks in Data Mining (Recurrent Neural Network) |
| 第 10 週 | Neural Networks in Data Mining (self-attention) |
| 第 11 週 | Neural Networks in Data Mining (Transformer) |
| 第 12 週 | No Class |
| 第 13 週 | Large Language Models in Data Mining |
| 第 14 週 | Graph Neural Network |
| 第 15 週 | Group Presentation (Asynchronous & No Class) |
| 第 16 週 | Final exam (No Class) |
教科書
Pang-Ning Tan, Michael Steinbach, and Vipin Kumar. Introduction to data mining. Pearson Education India, 2016.
Office Hours
- 時間
- by appointment
- 聯絡方式
- by e-mail