機器學習在教育上的應用
The Application of Machine Learning in Education
| 節 | 週二 |
|---|---|
5 13:20–14:10 | 機器學習在教育上的應用 CS 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
課程介紹: This introductory course covers fundamental concepts, techniques, and algorithms in machine learning, beginning with overviews on topics such as linear regression, classification, unsupervised learning and ending up with more recent topics such as deep neural networks. The course will guide students to understand the basic ideas and insights behind the design of advanced machine learning algorithms as well as some rationale of why a model works and how to use a model properly. 課程目標: - Understand what a machine can learn from data and basic learning strategies. - Be able to formulate machine learning problems corresponding to the application contexts. - Understand a variety of machine learning algorithms and their pros and cons. - Have a basic theoretical knowledge of machine learning approaches. - Be able to apply machine learning algorithms to solve problems.
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Quiz (10%) Homework (30%) Final project (50%) Participation and discussion (10%)
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| 週次 | 主題 |
|---|---|
| 第 1 週 | Course introduction; What is machine learning |
| 第 2 週 | Supervised learning; Unsupervised learning; Quiz 1 |
| 第 3 週 | Regression; Homework 1 |
| 第 4 週 | Classification; Quiz 2 |
| 第 5 週 | Clustering; Homework 2 |
| 第 6 週 | Dimensionality reduction; Quiz 3 |
| 第 7 週 | Neural networks; Homework 3 |
| 第 8 週 | Introduction to deep learning; Quiz 4 |
| 第 9 週 | Project: defining a problem |
| 第 10 週 | Project: data preparation |
| 第 11 週 | Project: model training and evaluation |
| 第 12 週 | Project: result visualization |
| 第 13 週 | Project: statistical analysis |
| 第 14 週 | Project: model optimization |
| 第 15 週 | Project: result interpretation |
| 第 16 週 | Final presentation |
| 第 17 週 | Final presentation |
| 第 18 週 | Final presentation |
Online resources
- 地點
- 人社一館 HA323
- 時間
- 請來信預約晤談時間
- 聯絡方式
- cwei@nctu.edu.tw