深度學習
Deep Learning
| 節 | 週四 |
|---|---|
N 12:20–13:10 | 深度學習 EC114（光復） 3 節連堂 |
5 13:20–14:10 | |
6 14:20–15:10 |
* 根據陽明交大上課時間表所列
(1) To understand the maths of deep learning techniques (2) To familiarize with deep learning tools, such as PyTorch, TensorFlow, etc. (3) To understand the latest developments and applications of deep learning techniques (4) To develop practical working systems Students requesting to add this course, please fill out the form.: https://forms.gle/6mQVbyLBo1B7Y1tCA
Linear Algebra, Probability Theory, Machine Learning (suggested)
無備註
分組方式 3人/組(Paper and Final) 1人/組(Lab) 師資人力 指導教師3人 助教8人 (1) To submit final projects as academic papers (2) To hold exhibition to showcase final projects (3) To encourage students to participate in various challenges in the fields of computer vision, gaming, data analytics, etc.
Part I (3 credits) - Deep Learning 4 Labs (including Labs 0, 2, 5, and 6) (done individually) 80% Final exam 20% Part II (3 credits) - Deep Learning Labs 4 Labs (including Labs 1, 3, 4, and 7) 50% Paper presentation (done in groups of 3 members) 25% Final project (done in groups of 3 members) 25%
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| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction & Machine Learning Basics 1. Linear Algebra 2. Probability and Information Theory |
| 第 2 週 | Deep Networks 1. Deep Feedforward Networks 2. Convolutional Networks |
| 第 3 週 | Convolutional Networks |
| 第 4 週 | Convolutional Networks & Transformers |
| 第 5 週 | Introduction to Reinforcement Learning |
| 第 6 週 | No class (清明連假) |
| 第 7 週 | 1. Linear Factor Models 2. Autoencoders |
| 第 8 週 | Valued Based Reinforcement Learning |
| 第 9 週 | Diffusion Models |
| 第 10 週 | Normalizing Flows |
| 第 11 週 | Policy-based Reinforcement Learning |
| 第 12 週 | Model-based Reinforcement Learning |
| 第 13 週 | Paper Presentation |
| 第 14 週 | Paper Presentation |
| 第 15 週 | Final Exam |
| 第 16 週 | Final Project Demo |
1. I. Goodfellow, Y. Bengio, and A. Courville,Deep Learning, 1st Ed., MIT Press, Dec.2016 2. R. S. Sutton and A. G. Barto, Reinforcement Learning: An Introduction, Nov. 2020
- 地點
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- 時間
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- 聯絡方式
- 老師 彭文孝wpeng@cs.nctu.edu.tw 陳永昇yschen@cs.nctu.edu.tw 謝秉均pinghsieh@cs.nycu.edu.tw 助教 楊賀弼mrrrimge32.cs13@nycu.edu.tw 劉子齊jonathan.tcliu.en11@nycu.edu.tw 温柏萱alison.cs13@nycu.edu.tw