機器學習
Machine Learning
| 節 | 週一 |
|---|---|
5 13:20–14:10 | 機器學習 EE132 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
Machine Learning is to understand the nature of (human and other forms of) learning, and to build learning capability in computers. To be more specific, there are three aspects of the goals of ML. (1) To make the computers smarter, more intelligent. The more direct objective in this aspect is to develop systems (programs) for specific practical learning tasks in application domains. (2) To dev elop computational models of human learning process and perform computer simulations. The study in this aspect is also called cognitive modeling. (3) To explore new learning methods and develop general learning algorithms independent of applications.
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homework 30% Mid. Term Report (Paper study, presentation, and report) 30% Final Project (Implementation) 40%
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction to Machine Learning |
| 第 1 週 | Least Squares |
| 第 3 週 | Linear Classification and Regression |
| 第 4 週 | Neural Networks and Back Propagation |
| 第 5 週 | Support Vector Machines |
| 第 6 週 | Support Vector Machines |
| 第 7 週 | Kernels and Mapping |
| 第 9 週 | Mid. Term - Paper Study & presentation |
| 第 10 週 | Mid. Term - Paper Study & presentation |
| 第 11 週 | Optimization Problem and Algorithm |
| 第 12 週 | Deep Learning -Convolution Neural Network |
| 第 13 週 | Bayesian Learning(貝葉斯學習) |
| 第 14 週 | Semi-supervised Learning |
| 第 15 週 | decision tree learning |
| 第 16 週 | Final Project presentation & Competition |
| 第 17 週 | Final Project presentation & Competition |
| 第 18 週 | Final Project presentation & Competition |
Deep Learning, Ian Goodfellow, Yoshua Bengio and Aaron Courville, 2016.
- 地點
- EE5 R761
- 時間
- 週二下午
- 聯絡方式
- E-mail: chleenctu@nctu.edu.tw Tel: 035-712121-54315