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Data Mining: Concepts and Techniques, 4th Edition by Jiawei Han, Micheline Kamber, and Jian Pei is a comprehensive guide to data mining principles, methods, and applications. It covers essential topics such as data preprocessing, classification, clustering, and association rule mining. The book provides a balance of theoretical foundations and practical techniques, making it useful for students, researchers, and professionals. This edition includes updates on big data analytics, deep learning, and data science applications. It features real-world examples, case studies, and exercises to reinforce learning. Published by Elsevier, it is widely used in academic and industry settings.
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Jiawei Han is a renowned computer scientist specializing in data mining, machine learning, and database systems. He is a professor at the University of Illinois at Urbana-Champaign and has authored numerous influential research papers. Han's work has significantly contributed to the development of data mining techniques and their real-world applications. He has received multiple awards for his contributions to computer science, including recognition from ACM and IEEE. His books, including Data Mining: Concepts and Techniques, are widely used in academia and industry. Han continues to advance the field through research, teaching, and mentorship.
About The Book
Data Mining: Concepts and Techniques, 4th Edition by Jiawei Han, Micheline Kamber, and Jian Pei is a comprehensive guide to data mining principles, methods, and applications. It covers essential topics such as data preprocessing, classification, clustering, and association rule mining. The book provides a balance of theoretical foundations and practical techniques, making it useful for students, researchers, and professionals. This edition includes updates on big data analytics, deep learning, and data science applications. It features real-world examples, case studies, and exercises to reinforce learning. Published by Elsevier, it is widely used in academic and industry settings.
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