Data Mining with Python: Theory, Application, and Case Studies

This book focuses on the hands-on approach to learning Data Mining. It showcases how to use Python Packages to fulfill the Data Mining pipeline, which is to collect, integrate, manipulate, clean, process, organize, and analyze data for knowledge.

本書專注於實踐式學習資料探勘。它展示了如何使用Python套件來完成資料探勘流程，包括收集、整合、操作、清理、處理、組織和分析資料以獲取知識。

Dr. Di Wu is an Assistant Professor of Finance, Information Systems, and Economics department of Business School, Lehman College. He obtained a Ph.D. in Computer Science from the Graduate Center, CUNY. Dr. Wu's research interests are 1) Temporal extensions to RDF and semantic web, 2) Applied Data Science, and 3) Experiential Learning and Pedagogy in business education. Dr. Wu developed and taught courses including Strategic Management, Databases, Business Statistics, Management Decision Making, Programming Languages (C++, Java, and Python), Data Structures and Algorithms, Data Mining, Big Data, and Machine Learning.

吳迪博士是雷曼學院商學院金融、資訊系統和經濟學系的助理教授。他在CUNY研究生中心獲得了計算機科學博士學位。吳博士的研究興趣包括：1）RDF和語義網的時間擴展，2）應用數據科學，以及3）商業教育中的體驗式學習和教學法。吳博士開發並教授了多門課程，包括戰略管理、數據庫、商業統計、管理決策、程式語言（C++、Java和Python）、數據結構和算法、數據挖掘、大數據和機器學習。