資料探勘與應用

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.

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

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