MATLAB進階程式設計與專題實作
MATLAB Advanced Programming Design
| 節 | 週四 |
|---|---|
7 15:30–16:20 | MATLAB進階程式設計與專題實作 YT203（陽明） 2 節連堂 |
8 16:30–17:20 |
* 根據陽明交大上課時間表所列
This course will introduce the concepts and applications of machine learning using MATLAB programming language. Students will learn the theoretical basis of machine learning from concept introduction, regression model, data classification, convolutional neural network to model selection and validation. We have MATLAB practice examples for demonstration. Students in this course will also use the content of this course to conduct project work, either through online data or their own research topics, in order to enhance their interest in computer science and machine learning, and to help them develop applications in their professional subjects.
It is required to have basic knowledge of MATLAB programming language.
無備註
Introduction to the course (1 week), introduction to machine learning concepts (2 weeks), regression models (2 weeks), data clustering (1 week), data classification (3 weeks), convolutional neural networks (2 weeks), model selection and validation (2 weeks), and final team project (3 weeks).
1. Attendance and participation: 30% 2. Midterm written proposal (1 to 2 pages): 30% 3. Final project report (oral presentation): 40%
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| 週次 | 主題 |
|---|---|
| 第 1 週 | Course introduction 2026-02-26(四) 時數：[2026-02-26]盧家鋒(2.00) |
| 第 2 週 | An overview of machine learning 2026-03-05(四) 時數：[2026-03-05]盧家鋒(2.00) |
| 第 3 週 | Representation of data for machine learning 2026-03-12(四) 時數：[2026-03-12]盧家鋒(2.00) |
| 第 4 週 | Linear and nonlinear regression 2026-03-19(四) 時數：[2026-03-19]盧家鋒(2.00) |
| 第 5 週 | Unsupervised learning: Clustering 2026-03-26(四) 時數：[2026-03-26]盧家鋒(2.00) |
| 第 6 週 | off (兒童節及民族掃墓節連假) 2026-04-02(四) |
| 第 7 週 | Classification: tree-based methods 2026-04-09(四) 時數：[2026-04-09]盧家鋒(2.00) |
| 第 8 週 | Classification: support vector machines 2026-04-16(四) 時數：[2026-04-16]盧家鋒(2.00) |
| 第 9 週 | MATLAB Graphic User Interface: App designer I 2026-04-23(四) 時數：[2026-04-23]盧家鋒(2.00) |
| 第 10 週 | MATLAB Graphic User Interface: App designer II 2026-04-30(四) 時數：[2026-04-30]盧家鋒(2.00) |
| 第 11 週 | Classification: neural networks 2026-05-07(四) 時數：[2026-05-07]盧家鋒(2.00) |
| 第 12 週 | Deep Learning & Convolutional neural networks 2026-05-14(四) 時數：[2026-05-14]盧家鋒(2.00) |
| 第 13 週 | MATLAB Deep Network Designer 2026-05-21(四) 時數：[2026-05-21]盧家鋒(2.00) |
| 第 14 週 | Deep Learning Applications (Object detection, Tumor segmentation, Image transformation) 2026-05-28(四) 時數：[2026-05-28]盧家鋒(2.00) |
| 第 15 週 | Resampling methods and model validation 2026-06-04(四) 時數：[2026-06-04]盧家鋒(2.00) |
| 第 16 週 | Final project report 2026-06-11(四) 時數：[2026-06-11]盧家鋒(2.00) |
[Textbook 1] A First Course in Machine Learning, 2nd edition, 2017 Simon Rogers, Mark Girolami CRC Press https://github.com/sdrogers/fcmlcode [Textbook 2] MATLAB Machine Learning Recipes, 2nd edition, 2018 Michael Paluszek, Stephanie Thomas Apress https://github.com/Apress/matlab-machine-learning-recipes [Textbook 3] An Introduction to Statistical Learning, 2nd edition, 2013 Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani Springer [Reference] Matlab Deep Learning Toolbox User's Guide, 2020 Mark Hudson Beale, Martin T. Hagan, Howard B. Demuth Mathworks
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