2 項進行中

115-1 選課時程

進行中

  • 初選第一階段 6/15 – 6/18
  • 初選第二階段 6/22 – 6/25
  • 校際選修 進行中 8/24 – 9/18
  • 初選第三階段 8/31 – 9/3
  • 開學後加退選 進行中 9/7 – 9/21
  • 逾期加退選 9/21 – 9/24
選課資源

加入行事曆

選擇訂閱 Google Calendar,或下載通用的 ICS 檔案。

使用 Google Calendar 時,Google 會收到這份課表的公開連結。

數位內容與機器學習

Digital Content and Machine Learning

學期
115-1
學分
3 學分
當期課號
537611
永久課號
MGIM30013
開課單位
人工智慧跨域學程-管理組、資訊管理研究所
授課教師
蔡銘箴
校區
光復
類別
選修
上課時間表
週三
5
13:20–14:10
數位內容與機器學習
MB304(光復)
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

概述

The course is to introduce the theoretical background of the digital content and the technique of content processing and applications. The class participants should be able to learn a broad and deep account of technology with an inside understanding of digital content, system and its practical implementation. Due to the recent progress of artificial intelligence and machine learning, the tools in MATLAB will be applied to learn the deep learning models, parameters optimization and not over-fitting for prediction accuracy. The applications will be introduced for time series analysis, pattern recognition in electronic commerce.

先修科目

Basic Computer Programming

備註

無備註

教學方式

Features of Teaching (design of materials, pedagogy, evaluation, resources and other facilities): Lectures are given in slides and HTML format. Grading: mid-term 20%; final exam 40%; class participation and home works 40%

評分方式

Features of Teaching (design of materials, pedagogy, evaluation, resources and other facilities): Lectures are given in slides and HTML format. Grading: mid-term 20%; final exam 40%; class participation and home works 40%

課程大綱
  • Special Topic Discussion

    1. content retrieval 2. interactivity 3. Latest progress

    講授:
    8
    示範:
    2
    實作:
    6
    其他:
    2
  • Course fundamental

    1. digital content introduction 2. multimedia data format 3. Image and Video 4. Audio

    講授:
    12
    示範:
    6
    實作:
    12
    其他:
    6
週次計畫
週次主題
第 1 週

Overview and Introduction

2026-09-09(三)
第 2 週

Fundamentals

2026-09-16(三)
第 3 週

Data presentation and transformation

2026-09-23(三)
第 4 週

Video and audio integration

2026-09-30(三)
第 5 週

Video editing techniques

2026-10-07(三)
第 6 週

MATLAB tools

2026-10-14(三)
第 7 週

MPEG1,MPEG2,MPEG4, H.264,MP3

2026-10-21(三)
第 8 週

Digital Right Management

2026-10-28(三)
第 9 週

Midterm report

2026-11-04(三)
第 10 週

Digital content implementation in electronic commerce

2026-11-11(三)
第 11 週

Machine learning introduction

2026-11-18(三)
第 12 週

Supervised Learning and non-supervised Learning

2026-11-25(三)
第 13 週

Neural network and deep learning architecture

2026-12-02(三)
第 14 週

The method of Optimization

2026-12-09(三)
第 15 週

Support Vector Machine Introduction

2026-12-16(三)
第 16 週

Convolutional Neural Network Introduction

2026-12-23(三)
第 17 週

Future techniques discussion

2026-12-30(三)
第 18 週

Final exam

2027-01-06(三)
教科書

Reference Book(s): 1. Digital Multimedia, Nigel Chapman and Jenny Chapman, John Wiley 2. Machine Learning in Python : Essential Techniques for Predictive Analysis, Michael Bowles, Wiley. 3. Handouts and selected journal papers

Office Hours
地點
MB304
時間
Tuesday CD
聯絡方式
Ext. 57406 e-mail: mjtsai@cc.nctu.edu.tw