資料科學
Data Science
| 節 | 週二 |
|---|---|
2 09:00–09:50 | 資料科學 EDB07（光復） 3 節連堂 |
3 10:10–11:00 | |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
This course will attempt to apply data mining, statistics, machine learning, information visualization, social network analysis, and text analysis techniques to gain new insight from data. Only minimal probability and statistics background is expected. We will survey the foundational and important topics in data science listed as follows. 1) Data Manipulation 2) Data Analysis with Statistics and Machine Learning 3) Data Communication with Information Visualization 4) Data at massive scale (big data analytics)
Prerequisites: Programming (C++, JAVA, or Python), Database, and Probability and Statistics *Knowledge of Python will be useful for the assignments
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Midterm: 30% Final Project (in groups): 27% Homework : 48% (6 @ 8% each) Class participation (up to 6 points)
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| 週次 | 主題 |
|---|---|
| 第 2 週 | Introduction to Data Science 2/27 |
| 第 3 週 | Intro Python / Data Crawling [HW1: Crawling Release] 3/6 |
| 第 4 週 | Data Mining (Frequent Pattern –Apriori + FP-Tree) 3/13 |
| 第 5 週 | Data Mining (Classification) [HW2: Data Mining] 3/20 |
| 第 6 週 | Data Mining (Classification) 3/27 |
| 第 7 週 | Data Mining (Clustering) + Evaluation 4/3 |
| 第 8 週 | Statistical Measurements/Feature Selection/Dimension Reduction [HW3: dimension reduction/feature selection] 4/10 |
| 第 9 週 | Machine Learning/Deep Learning 4/17 |
| 第 10 週 | Midterm 4/24 |
| 第 11 週 | Deep Learning [HW4] 5/1 |
| 第 12 週 | Multimedia Processing 5/8 |
| 第 13 週 | NLP [HW5] 5/15 |
| 第 14 週 | Invited Talk 5/22 |
| 第 15 週 | Graph Theory/SN analysis [HW6] 5/29 |
| 第 16 週 | Graph Theory/SN analysis 6/5 |
| 第 17 週 | Final presentation 6/12 |
| 第 18 週 | Final presentation 6/19 |
There is no single textbook. However, a couple of books that are useful and helpful are listed below: (1) Introduction to Data Mining, by P.-N. Tan, M. Steinbach, V. Kumar, 2005 (ISBN:0321321367) (2) Doing Data Science, by C. O'Neil and R. Schutt, 2013 (ISBN: 978-1-4493-5865-5) (3) Python for Data Analysis, by W. McKinney, 2012 (ISBN: 978-1-4493-1979-3)
- 地點
- ED-807
- 時間
- 2 pm - 4 pm every Tuesday
- 聯絡方式
- TEL:(03)571-2121#54530 EMAIL: hhshuai@nctu.edu.tw