深度學習
Deep Learning
| 節 | 週二 |
|---|---|
5 13:20–14:10 | 深度學習 ED219（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
Deep learning is a branch of machine learning and recently receive a lot of attention due to its state-of-the art performance. Deep learning has been applied extensively to many areas such as computer vision, speech recognition, natural language processing, bioinformatics, and wireless networks. In this course, we will introduce various deep learning architectures and techniques, and discuss the advances in this area through paper presentation (by students). Students have the chance to practice implementing deep learning by doing programming homework and applying deep learning to real problems by doing final project.
Probability, linear algebra, machine learning (preferred but not required)
無備註
教師未提供此項資料
Homework (programming): 30% Paper presentation: 20% Midterm exam: 30% Final project: 20%
Introduction to machine learning
Deep feedforward networks
Regularization for deep learning
Optimization for training deep models
Convolutional networks
Recurrent and recursive networks
Autoencoders
Deep generative models
Reinforcement learning
| 週次 | 主題 |
|---|---|
| 第 1 週 | 2026-09-08(二) |
| 第 2 週 | 2026-09-15(二) |
| 第 3 週 | 2026-09-22(二) |
| 第 4 週 | 2026-09-29(二) |
| 第 5 週 | 2026-10-06(二) |
| 第 6 週 | 2026-10-13(二) |
| 第 7 週 | 2026-10-20(二) |
| 第 8 週 | 2026-10-27(二) |
| 第 9 週 | 2026-11-03(二) |
| 第 10 週 | 2026-11-10(二) |
| 第 11 週 | 2026-11-17(二) |
| 第 12 週 | 2026-11-24(二) |
| 第 13 週 | 2026-12-01(二) |
| 第 14 週 | 2026-12-08(二) |
| 第 15 週 | 2026-12-15(二) |
| 第 16 週 | 2026-12-22(二) |
I. Goodfellow and Y. Bengio and A. Courville, Deep Learning, The MIT Press, 2016
- 地點
- By appointment
- 時間
- By appointment
- 聯絡方式
- chiahan@nycu.edu.tw