資料探勘
Data Mining
| 節 | 週二 |
|---|---|
5 13:20–14:10 | 資料探勘 EC114（光復） 2 節連堂 |
6 14:20–15:10 |
* 根據陽明交大上課時間表所列
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. (This course is taught in English.)
Machine Learning, Artificial Intelligence, Python Programming
無備註
上課以投影片內容為主,並指派作業作為實作練習。
3 homework、1 term project、1 group presentation Homework:60% Final project:30% Group presentation:10%
Association Analysis
1.Association Rule Mining 2. Apriori Algorithm
Regression
Linear Regression
Classification
1. Decision Tree 2. Support Vector Model 3. Logistic Regression
Deep Learning for Data Mining
1. Neural networks 2. Transformer 3. Graph neural network
Introduction to Data Mining
1. Basic concepts of data 2. Data Preprocessing 3. Applications of Data Mining
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction of the Course 2023-02-14(二) |
| 第 2 週 | Introduction to Data Mining 2023-02-21(二) |
| 第 3 週 | No class 2023-02-28(二) |
| 第 4 週 | Association Analysis 2023-03-07(二) |
| 第 5 週 | Regression 2023-03-14(二) |
| 第 6 週 | Classification (Basic Concepts and Techniques) 2023-03-21(二) |
| 第 7 週 | Neural Networks in Data Mining (DNN) 2023-03-28(二) |
| 第 8 週 | Neural Networks in Data Mining (CNN, LSTM) 2023-04-04(二) |
| 第 9 週 | Midterm (No Class) 2023-04-11(二) |
| 第 10 週 | Neural Networks in Data Mining (Transformer) 2023-04-18(二) |
| 第 11 週 | Anomaly Detection 2023-04-25(二) |
| 第 12 週 | Clustering and Dimension Reduction Advanced techniques (Text Mining) 2023-05-02(二) |
| 第 13 週 | Graph Neural Network 2023-05-09(二) |
| 第 14 週 | Graph Neural Network 2023-05-16(二) |
| 第 15 週 | Break for Final Project 2023-05-23(二) |
| 第 16 週 | Break for Final Project 2023-05-30(二) |
| 第 17 週 | Group presentation 2023-06-06(二) |
| 第 18 週 | Group presentation 2023-06-13(二) |
Pang-Ning Tan, Michael Steinbach, and Vipin Kumar. Introduction to data mining. Pearson Education India, 2016.
- 地點
- 教師未提供此項資料
- 時間
- by appointment
- 聯絡方式
- by e-mail