機器學習入門與應用
Machine Learning: Foundations and Applications
| 節 | 週四 |
|---|---|
2 09:00–09:50 | 機器學習入門與應用 CS105（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 introduces the concepts and implementations of the most important machine learning approaches used in data analysis and prediction, covering both mathematical theorems and practical applications. All machine learning models will be described with several worked examples and case studies. This course also introduces the basic concepts of artificial neural networks and deep learning. * Class time: 9:30-12:00 (no break). * All lectures take place in the classroom, not online. * 上課時間：9:30-12:00，中間不下課。 * 實體上課，無線上上課。
Basic Python programming skills.
無備註
教師未提供此項資料
homework: 60% final project: 40%
教師未提供此項資料
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction 2026-09-10(四) |
| 第 2 週 | Simple machine learning 2026-09-17(四) |
| 第 3 週 | Artificial neural networks 2026-09-24(四) |
| 第 4 週 | Artificial neural networks/CNN 2026-10-01(四) |
| 第 5 週 | CNN 2026-10-08(四) |
| 第 6 週 | Evaluation 2026-10-15(四) |
| 第 7 週 | Regression Models 2026-10-22(四) |
| 第 8 週 | Regression Models 2026-10-29(四) |
| 第 9 週 | Similarity-based learning 2026-11-05(四) |
| 第 10 週 | Similarity-based learning and PCA 2026-11-12(四) |
| 第 11 週 | Decision trees & random forest 2026-11-19(四) |
| 第 12 週 | Probability-based Learning 2026-11-26(四) |
| 第 13 週 | SVM 2026-12-03(四) |
| 第 14 週 | Unsupervised learning 2026-12-10(四) |
| 第 15 週 | Final projection presentation 2026-12-17(四) |
| 第 16 週 | Final projection presentation 2026-12-24(四) |
[1] John D. Kelleher, Brian Mac Namee and Aoife D'Arcy, Fundamentals of Machine Learning for Predictive Data Analytics, 2nd, MIT Press, 2020. [2] Aurélien Géron. Hands-On Machine Learning with Scikit-Learn and PyTorch. O'Reilly, 2022.
- 地點
- CS 331
- 時間
- By appointment
- 聯絡方式
- jameschengcs@nycu.edu.tw