NCHU Course Outline
Course Name (中) 數據挖掘與視覺化(6956)
(Eng.) Data Mining and Visualization
Offering Dept Graduate Institute of Data Science and Information Computing
Course Type Elective Credits 3 Teacher Ching-Ting Tu
Department Doctoral Program in Big Data Analytics for Industrial Applications / Ph.D Language Chinese Semester 2025-FALL
Course Description 課程內容將機器學習型(深度學習)理論為基礎應用於視覺語意探索。課程整合線性代數、機率統計與程式設計為基礎,介紹機器學習模型背後含有的數學原,這些機器學習方法包含:線性回歸、主成分分析、及支持向量分類和分群問題。
本課程期待培養學生於電腦視覺及機器學習領域技術設計及整合實作的能力,透過視覺探索實際應用之實作來培育學生具備研發思考、程式設計及解決現存問題的能力,並可把所學的數學理論基礎應用到工業界實務面。
Prerequisites
Relevance of Course Objectives and Core Learning Outcomes(%) Teaching and Assessment Methods for Course Objectives
Course Objectives Competency Indicators Ratio(%) Teaching Methods Assessment Methods
1. Python 程式實作能力
2. 機器學習於影像語意(矩陣)探索與搜尋
3. 機器學習方法於影像訊號實務應用與分析
1.Mathematical Thinking and Logic
2.Artificial Intelligence Theory and Application Expertise
3.Expertise in Big Data Theory and Applications
40
30
30
topic Discussion / Production
Exercises
Discussion
Lecturing
Assignment
Quiz
Internship
Course Content and Homework/Schedule/Tests Schedule
Week Course Content
Week 1 課程介紹&電腦視覺
Week 2 新南向演講 +Python 基礎影片
Week 3 NN&CNN classifier-(I)
Week 4 NN&CNN classifier-(II)
Week 5 License plate correction &recognition(車牌辨識與校正)-I-Bayesian Classifier
Week 6 License plate correction &recognition(車牌辨識與校正)-II
Week 7 paper-disscusssion: cnn&histigram&affine
programming quizzes (Python): affine& histogram &cnn code
Week 8 Adaboost 分類(相機人臉偵測)_1
Week 9 Adaboost 分類(相機人臉偵測)_2
Week 10 paper-disscusssion: cnn&Adaboost
programming quizzes (Python):Adaboost&Bayesian
Week 11 Object tracking (物件追蹤): SVM (support vector machine) --線上課程
Week 12 Face recognition- PCA (人臉識別) (Principal Component Analysis)/LDA (Linear Discriminant Analysis) (I)
Week 13 Face recognition- PCA (人臉識別) (Principal Component Analysis)/LDA (Linear Discriminant Analysis) (II)
Week 14 paper-disscusssion :cnn&SVM
paper-disscusssion:cnn&PCA
programming quizzes (Python) *1: PCA
Week 15 期末 Exam
Week 16 放假 (繳交 錄影期末報告)
video (ppt+program demo)
self-directed
learning
   03.Preparing presentations or reports related to industry and academia.

Evaluation
1 次正式考試: 15*1=15%
4 次paper report: 15%
5 次程式小考 (Python) 7*5=35%
1 次期末分組報告+demo : 25%
Q&A (Slido) 或筆記繳交:10%
Textbook & other References
上課講義與網路資料
Teaching Aids & Teacher's Website
https://sites.google.com/site/cvlabhomepage/course-ke-cheng/%E6%95%B8%E6%93%9A%E6%8C%96%E6%8E%98%E8%88%87%E8%A6%96%E8%A6%BA%E5%8C%96-%E7%A2%A9%E5%A3%AB2025
Office Hours
預約
Sustainable Development Goals, SDGs(Link URL)
include experience courses:N
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Update Date, year/month/day:2025/09/18 11:55:09 Printed Date, year/month/day:2026 / 9 / 13
The second-hand book website:http://www.myub.com.tw/