一、課程基本資料 Course Information | ||||||||||||||||||||||||||||||||||||||||
科目名稱 Course Title: (中文)機器學習導論 (英文)INTRODUCTION TO MACHINE LEARNING WITH R |
開課學期 Semester:108學年度第1學期 開課班級 Class:經三A |
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授課教師 Instructor:米克里斯多 MICHALOPOULOS, CHRISTOS | ||||||||||||||||||||||||||||||||||||||||
科目代碼 Course Code:BEC36901 | 單全學期 Semester/Year:單 | 分組組別 Section: | ||||||||||||||||||||||||||||||||||||||
人數限制 Class Size:40 | 必選修別 Required/Elective:選 | 學分數 Credit(s):2 | ||||||||||||||||||||||||||||||||||||||
星期節次 Day/Session: 一56 | 前次異動時間 Time Last Edited:108年06月20日00時07分 | |||||||||||||||||||||||||||||||||||||||
經濟學系基本能力指標 Basic Ability Index | ||||||||||||||||||||||||||||||||||||||||
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二、指定教科書及參考資料 Textbooks and Reference (請修課同學遵守智慧財產權,不得非法影印) |
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●指定教科書 Required Texts My lecture notes. No need to buy a textbook! ●參考書資料暨網路資源 Reference Books and Online Resources I will give a list in the class. | ||||||||||||||||||||||||||||||||||||||||
三、教學目標 Objectives | ||||||||||||||||||||||||||||||||||||||||
In this class, students will learn the basics of machine learning using R (free software). They will learn data mining and machine learning techniques which help discover previously unknown patterns and relationships in data. Machine learning is a collection of sophisticated mathematical algorithms used to segment the data and predict the likelihood of future events based on past events. In this class, many such algorithms will be explained simply and with many examples with real data for students to learn how to use such techniques on their own. After this class, students will be confident enough to use the tools learned and even go deeper by reading more mathematically oriented textbooks on machine learning. They will gain important experience in analyzing many types of data using a variety of statistical techniques and algorithms that might be valuable for his/her future employment as a data analyst in any type of industry. |
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In this class, students will learn the basics of machine learning using R (free software). They will learn data mining and machine learning techniques which help discover previously unknown patterns and relationships in data. Machine learning is a collection of sophisticated mathematical algorithms used to segment the data and predict the likelihood of future events based on past events. In this class, many such algorithms will be explained simply and with many examples with real data for students to learn how to use such techniques on their own. After this class, students will be confident enough to use the tools learned and even go deeper by reading more mathematically oriented textbooks on machine learning. They will gain important experience in analyzing many types of data using a variety of statistical techniques and algorithms that might be valuable for his/her future employment as a data analyst in any type of industry. |
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四、課程內容 Course Description | ||||||||||||||||||||||||||||||||||||||||
●整體敘述 Overall Description |
●分週敘述 Weekly Schedule
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五、考評及成績核算方式 Grading | ||||||||||||||||||||
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六、授課教師課業輔導時間和聯絡方式 Office Hours And Contact Info | ||||||||||||||||||||
●課業輔導時間 Office Hour 課堂告知 |
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●聯絡方式 Contact Info
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七、教學助理聯絡方式 TA’s Contact Info | |||||
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八、建議先修課程 Suggested Prerequisite Course | |||||
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九、課程其他要求 Other Requirements | |||||
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十、學校教材上網及教師個人網址 University’s Web Portal And Teacher's Website | |||||
學校教材上網網址 University’s Teaching Material Portal: 東吳大學Moodle數位平台:http://isee.scu.edu.tw |
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教師個人網址 Teacher's Website: | |||||
其他 Others: | |||||
十一、計畫表公布後異動說明 Changes Made After Posting Syllabus | |||||