資料探勘與應用

114學年第1學期 英語授課 選修課 3 學分
授課大綱
50
名額
13
已選
37
餘額
上課時間
一/2,3,4[遠距課程]
授課教師
Office Hour:晤談時間:上課前後10分鐘 地點:上課教室
修課班級
共選修3,4,碩博1,2 · 1年級以上
課程資訊
教育部補助臺灣大專院校人工智慧學程聯盟,開設學校:清華大學(陳宜欣),同步遠距上課時間:星期一 9:00~12:00,開放大三以上修習,英文授課,遠距課程
選課分析

Two assignments 20
·One short presentation 10
One project 25
·One exam 35
Class participation (in or after class) 10

Data mining serves as a crucial field that leverages advanced algorithms to reveal hidden, yet invaluable insights buried within extensive datasets. These algorithms are drawn from a multitude of areas such as machine learning, artificial intelligence, pattern recognition, statistics, and database systems, working together to facilitate a deeper understanding and analysis of data. This course is designed to equip you with the foundational knowledge and hands- on experience needed to delve into the expansive world of data mining. Whether you are looking to enhance your skill set or embark on a new career path, this course will serve as a stepping stone to achieving your goals. The curriculum encompasses a range of topics that will introduce you to the core concepts and techniques prevalent in the field of data mining. These include: ·Association Rules: Understand the principles behind identifying rules that highlight relationships between seemingly independent data in a database. ·Clustering: Learn about grouping a set of objects in such a way that objects in the same group are more similar to each other than to those in other groups. ·Classification: Gain knowledge on the procedures for identifying the predefined class of a new observation. ·Text Mining: Equip yourself with the skills needed to analyze and interpret large collections of text data to extract meaningful information. · Data Mining Applications: Explore the various practical applications of data mining across different industries and sectors.

Pang-Ning Tan, Michael Steinbach, Vipin Kumar, Introduction to Data Mining,
Addison Wesley

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