資料科學應用
Data Science Applications
| 節 | 週二 |
|---|---|
5 13:20–14:10 | 資料科學應用 MB414（光復） 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
The objective of this class focus on data science applications, including text mining, sales forecasting, prognostics and health management and health care. Selected papers are available for the students to study. The students should complete final reports related to these topics.
事先修過資料分析 (DEM1201)或進階資料分析(IEM5251)
無備註
教師未提供此項資料
評量方法 Paper Survey or Project (40%), Presentation & Discussion (40%), Others (20%)
Text Mining & Sales Forecasting
1. Working with text documents 2. Opinion Mining 3. Regression Analysis 4. Locally Weighted Regression
Prognostics and Health Management & Health care
1. Time-series Data Analysis 2. Data-driven Prognostics 3. Tree-based Methods 4. Pattern Discovery
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction to the course |
| 第 2 週 | Text Mining Overview |
| 第 3 週 | Text Classification |
| 第 4 週 | Text Classification |
| 第 5 週 | Opinion Mining |
| 第 6 週 | Text Clusteering |
| 第 7 週 | EM Algorithm |
| 第 8 週 | Topic Modeling |
| 第 9 週 | Word Embedding |
| 第 10 週 | Project Presentation |
| 第 11 週 | Convolutional Neural Networks |
| 第 12 週 | Time Series Data Analysis |
| 第 13 週 | Imbalanced Data |
| 第 14 週 | Project Presentation |
| 第 15 週 | Anomaly Detection |
| 第 16 週 | Forecasting |
| 第 17 週 | RNN/LSTM |
| 第 18 週 | Final Presentation & Report |
1. Data Mining: Concepts and Techniques, 3rd ed., Morgan Kaufmann Publishers, 2011, by Jiawei Han and Micheline Kamber 2. Introduction to Data Mining, Addison-Wesley, 2006 by Pang-Ning Tan, Michael Steinbach and Vipin Kumar 3. Paper Reading
- 地點
- 505R
- 時間
- TBD
- 聯絡方式
- Email: clliu@mail.nctu.edu.tw