基本素養 Basic Literacy
無核心能力 Competence
■ 船舶或機電系統工程的高階專業知識與創新之能力。
High level professional knowledge & creativeness for naval or mechatronic engineering.
□ 策劃、執行專題研究及呈現研究成果之能力。
Administer and make plans for case study & present the research results.
□ 撰寫專業論文的能力。
Writing professional papers.
■ 創新思考及獨立解決問題的能力。
Innovative thinking and independent problem solving.
□ 跨領域協調整合之能力。
Multidisciplinary teamwork.
□ 良好的國際觀。
Well international outlook.
□ 管理、規劃及領導的能力。
Management, planning and leadership.
□ 持續自我學習成長的能力。
Continuous learning self.
課程概述 Course Description
本課程主要讓學生學習幾種常用的機器學習理論與方法，同時根據所學得的知識解決實務上的問題。Students are expected to learn multiple machine learning models and understand some of the issues and challenges facing attempts at machine learning while being exposed to the pragmatics of implementing machine learning systems.
課程學習目標 Course Objectives
課程進度 Progress Description
| 進度說明 Progress Description | |
|---|---|
| 1 | Introduction |
| 2 | Regression analysis |
| 3 | Regression analysis |
| 4 | Principal component analysis (PCA) |
| 5 | Principal component analysis (PCA) |
| 6 | 1st Midterm exam |
| 7 | Decision trees |
| 8 | Decision trees |
| 9 | Hierarchical clustering |
| 10 | Nearest-neighbor classifiers |
| 11 | K-means |
| 12 | 2nd Midterm exam |
| 13 | Singular value decomposition (SVD) |
| 14 | Singular value decomposition (SVD) |
| 15 | artificial neural network |
| 16 | artificial neural network |
| 17 | artificial neural network |
| 18 | Final exam |
以上每週進度教師可依上課情況做適度調整。The schedule may be subject to change.
有關課程其他調查 Other Surveys of Courses
1.本課程是否規劃業界教師參與教學或演講?Is there any industry specialist invited in this course? How many times?
2.本課程是否規劃含校外實習(並非參訪)?
Are there any internships involved in the course? How many hours?
3.本課程是否可歸認為學術倫理課程? 否
Is this course recognized as an academic ethics course? In the course how many hours are regarding academic ethics topics? No
4.本課程是否屬進入社區實踐課程?
Is this course recognized as a Community engagement and Service learning course? Which community will be engaged?