
BOOKS - OS AND DB - Data Mining Theories, Algorithms, and Examples

Data Mining Theories, Algorithms, and Examples
Author: Nong Ye
Year: 2013
Pages: 349
Format: PDF
File size: 4 MB
Language: ENG

Year: 2013
Pages: 349
Format: PDF
File size: 4 MB
Language: ENG

Book Description: The book "Data Mining Theories Algorithms and Examples" by Tan, Bang Pham, and Le Thi Thu provides a comprehensive overview of data mining techniques and their applications in various fields. The authors present a systematic approach to understanding the concepts and algorithms of data mining, making it accessible to readers who may not have a technical background in computer science or statistics. The book covers topics such as data preprocessing, data warehousing, OLAP, data mining functions, and advanced data mining techniques like neural networks and deep learning. It also includes examples and case studies to illustrate the practical applications of data mining in industries like finance, marketing, and healthcare. Long Detailed Description: In today's fast-paced technological world, it is essential to understand the process of technology evolution and its impact on humanity. The book "Data Mining Theories Algorithms and Examples" by Tan, Bang Pham, and Le Thi Thu offers a unique perspective on this topic by exploring the intersection of data mining and human survival. The authors argue that developing a personal paradigm for perceiving the technological process of modern knowledge is crucial for the survival of humanity and the unification of people in a warring state. This book provides a comprehensive guide to data mining theories, algorithms, and examples, making it an indispensable resource for anyone looking to gain a deeper understanding of the field. The book begins with an introduction to data mining, explaining the importance of this field and its relevance to various industries. The authors then delve into the fundamentals of data preprocessing, which is a critical step in the data mining process.
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