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2024年9月6日 星期五

資料探勘與應用 Data Mining : Concepts, Techniques, and Applications (Sylabus)



數據探勘 (Data Mining) 是一個關鍵領域,利用先進的算法揭示隱藏在龐大數據集中無價的洞察力。這些算法來自多個領域,如機器學習、人工智能、模式識別、統計學和資料庫系統,共同促進對數據的深入理解和分析。

本課程旨在為您提供數據探勘的基礎知識和實際操作經驗。無論您是希望提升技能還是開闢新的職業道路,本課程都將成為實現目標的踏腳石。課程涵蓋的主題範圍廣泛,將引導您進入數據探勘領域的核心概念和技術,包括:

  • 關聯規則(Association Rules):了解識別數據庫中看似獨立數據之間關係的規則背後的原理。
  • 聚類(Clustering):學習如何將一組對象進行分組,使同一組內的對象彼此之間的相似度高於與其他組內對象的相似度。
  • 分類(Classification):掌握識別新觀察對象的預定類別的過程。
  • 文本挖掘(Text Mining):學習如何分析和解釋大量文本數據,以提取有意義的信息。
  • 數據挖掘應用(Data Mining Applications):探索數據挖掘在不同產業和部門中的各種實際應用。
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.



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