基本素養 Basic Literacy

領導能力
學生應具備領導其他專長同仁解讀數據的才能
Leadership
Undergraduate students should develop leadership skills required of a person in a leading position
倫理及社會責任
學生需有自我學習的的意願及能力,並積極參與活動以擴大其社交網絡
Ethic & Social Responsibility
Undergraduate students should demonstrate ethical awareness in learning and in social networking
全球化視野
同學需適時的掌握現在國際間情勢的更替,並理解全球化的趨勢
Global Awareness
Undergraduate students should possess a global perspective and an awareness of the effects of globalization

核心能力 Competence

口頭溝通及表達能力
學生應具備基本的口語表達能力,能迅速的將事情完整地表達出來
Oral Communication/ Speaking
Undergraduate students should be able to communicate effectively in speaking.
寫作表達能力
學生應具備基本的寫作表達能力,能迅速的將事情完整地表達出來
Written Communication/Writing
Undergraduate students should be able to communicate effectively in writing.
創造及創新能力
同學需要有能力依據不同型態地問題及資料將所學做有效的及創新的整合以利問題的解決
Creativity and Innovation
Undergraduate students should be able to solve strategic problems with creative and innovative approaches
解決問題能力
同學需要有能力依據不同型態地問題及資料將所學做有效的及創新的整合以利問題的解決
Problem Solving
Undergraduate students should be able to solve strategic problems with creative and innovative approaches
分析及計算能力
同學需要有能力依據不同型態地問題及資料將所學做有效的及創新的整合以利問題的解決
Analytical & Computational Skills
Undergraduate students should be able to solve strategic problems with creative and innovative approaches
價值、技巧及專業度
學生能在其工作崗位上,貢獻其所學在統計分析上之專業知識,以冀望能取得在職場上對其統計專業的認同
Values, Skills & Professionalism
Undergraduate students should acquire the skills and values required of a true professional
專業能力
學生能在其工作崗位上,貢獻其所學在統計分析上之專業知識,以冀望能取得在職場上對其統計專業的認同
Technical Skills
Undergraduate students should acquire the skills and values required of a true professional
管理技巧
學生能在其工作崗位上,貢獻其所學在統計分析上之專業知識,以冀望能取得在職場上對其統計專業的認同
Management Skills
Undergraduate students should acquire the skills and values required of a true professional

課程概述 Course Description

機器學習是一門新近的熱門研究領域,主要探討如何在高維度、大量或複雜資料中,使用統計方法來發展不同的演算法來發掘資料中所隱藏的有用資訊。
Machine Learning is a popular research area lately. The main goal is to investigate the high dimensional, large amount or complex data, and use statistical methods to develop the useful algorithm to discover information within data.

課程學習目標 Course Objectives

  • Students will learn different methods in Machine Learning.
  • Students are able to analyze massive and complicate data.
  • Students are capabale to do programing for different algorithms.
  • 課程進度 Progress Description

    進度說明 Progress Description
    1Introduction
    2Statistical Learning
    3Linear Regression
    4Linear Regression
    5Classification
    6Classification
    7Classification
    8Resampling Methods
    9Resampling Methods
    10Linear Model Selection and Regularization
    11Linear Model Selection and Regularization
    12Moving Beyond Linearity
    13Tree-Based Methods and Project Report
    14Tree-Based Methods
    15Support Vector Machines
    16Support Vector Machines
    17Unsupervised Learning
    18Project Report
     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? 否
    Is there any industry specialist invited in this course? How many times? No
    2.本課程是否規劃含校外實習(並非參訪)? 否
    Are there any internships involved in the course? How many hours? No
    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? 否
    Is this course recognized as a Community engagement and Service learning course? Which community will be engaged? No