| 課程編碼 Course Code | 中文課程名稱 Course Name (Chinese) | 英文課程名稱 Course Name (English) | 總學分數 Credits | 總時數 Hours |
|---|---|---|---|---|
| 6105061 | 機器學習 | Machine Learning | 3.0 | 3 |
| 中文概述 Chinese Description | 本課程以論文研討方式學習 "機器學習" 理論之基本概念與應用及各種演算法。課程內容包含概念式學習、決策樹、圖型理論、神經網路、貝氏網路、案例式學習及支持向量機等方法。經由這門課，學生能對現代機器學習技術及其應用有基本的了解。 | |||
| 英文概述 English Description | This is a graduate seminar-based course that provides an overview of many algorithms in machine learning and its applications. In this course, we will take an interdisciplinary look at current research topics in machine learning covering Concept Learning, Decision Tree, Graphical Model, Neural Network, Bayesian Network, Instance-based Learning, and Support Vector Machine. Through the course, students can have the basic ideas and intuition behind modern machine learning methods. | |||
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