機器學習
Machine Learning
| 節 | 週一 |
|---|---|
5 13:20–14:10 | 機器學習 EE208 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
In this course, to enable students to understand the application of machine learning and the theoretical background and programming of machine learning and evaluate how to use appropriate algorithms in practical examples. Topics cover the recent machine learning models.
Linear algebra, probability, fundamental calculus, programming (Python, Matlab, Tensorflow, etc.), optimization EECN30124), highly recommended!
TA: TBD
Lab assignments 36% Mid-term exam 34% Final project 30%
| 週次 | 主題 |
|---|---|
| 第 1 週 | ML fundamentals |
| 第 2 週 | Math of ML |
| 第 3 週 | Regression |
| 第 4 週 | Classification |
| 第 5 週 | CNN |
| 第 6 週 | LSTM |
| 第 7 週 | Transformer |
| 第 8 週 | Mid-term |
| 第 9 週 | VAE |
| 第 10 週 | GAN |
| 第 11 週 | Diffusion model |
| 第 12 週 | Intro to RL |
| 第 13 週 | A3C |
| 第 14 週 | DDPG |
| 第 15 週 | PPO |
| 第 16 週 | Final project |
1. Christopher M. Bishop , Hugh Bishop. Deep Learning - Foundations and Concepts, Springer Cham, 2024. 2. E. Alpaydin. Introduction to machine learning. Cambridge, MA: MIT Press, 2004. 3. Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar. Foundations of machine learning. MIT press, 2018. 4. C. Bishop "Pattern Recognition and Machine Learning (Information Science and Statistics), 1st edn. 2006. corr. 2nd printing edn." (2007). 5. Sergios Theodoridis. Machine Learning: A Bayesian and Optimization Perspective. Elsevier Ltd, 2015. 6. Sebastian Raschka, Python machine learning. Packt publishing ltd, 2015.
- 地點
- EE749
- 時間
- Monday, 11am-12pm
- 聯絡方式
- Tel: 03-5712121 ext54345 or Email: sofin@nycu.edu.tw