Comprehensive coverage of data mining concepts and techniques, including data preprocessing, classification, clustering, and association rule mining. Essential resource for students, researchers, and professionals in data mining, machine learning, and data analysis.
Technical TutorialsData ScienceMachine Learning
Introduction
Data Mining Concepts and Techniques by Jiawei Han, Micheline Kamber, and Jian Pei provides an in-depth exploration of data mining concepts, techniques, and applications in the field of machine learning and data analysis. The book covers topics such as data preprocessing, classification, clustering, and association rule mining, offering valuable insights into the principles and methods of data mining.
Highlights
Comprehensive coverage of data mining concepts and techniques
Detailed exploration of topics such as data preprocessing, classification, clustering, and association rule mining
Valuable insights into the principles and methods of data mining
Applicable to a wide range of machine learning and data analysis tasks
Recommendation
This book is highly recommended for students, researchers, and professionals interested in data mining, machine learning, and data analysis. It provides a solid foundation in the key concepts and techniques of data mining, making it an essential resource for anyone looking to deepen their understanding of this rapidly evolving field.