DATA MINING & WAREHOUSING TECH MACHINE LEARNING CONCEPTS

Vijayakumar P

ISBN 10: 9819803128 / ISBN 13: 9789819803125

Editore: World Scientific, 2025

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nach der Bestellung gedruckt Neuware - Printed after ordering - This unique compendium elaborates the basic perceptions of data warehouses and data mining. The former part of the book covers concepts like introduction to data warehouses, the need for using such data warehouses and key terminologies used in this framework. The latter part of the book covers the data mining concepts and the data mining techniques used in various applications and also explains the machine learning techniques in detail with suitable examples wherever essential.The book is written in simple English and is user-friendly. Each chapter is modeled with several sample scenarios and illustrations wherever necessary. The complete contents of each chapter include chapter technical content, summary, key points to remember, and few case studies for class group discussions and problem-solving.This volume clearly benefits professionals, academicians, data analysts, machine-learning community, undergraduate and postgraduate students.

Codice articolo 9789819803125

Dati bibliografici

• Titolo: DATA MINING & WAREHOUSING TECH MACHINE LEARNING CONCEPTS
• Editore: World Scientific
• Data di pubblicazione: 2025
• Lingua: Inglese
• ISBN 10: 9819803128
• ISBN 13: 9789819803125
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 235 L x 157 A x 33 P (millimetri) 235 millimetri di larghezza per 157 millimetri di altezza per 33 millimetri di profondità
• Peso: 913 grammi

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Riassunto

This unique compendium elaborates the basic perceptions of data warehouses and data mining. The former part of the book covers concepts like introduction to data warehouses, the need for using such data warehouses and key terminologies used in this framework. The latter part of the book covers the data mining concepts and the data mining techniques used in various applications and also explains the machine learning techniques in detail with suitable examples wherever essential. The book is written in simple English and is user-friendly. Each chapter is modeled with several sample scenarios and illustrations wherever necessary. The complete contents of each chapter include chapter technical content, summary, key points to remember, and few case studies for class group discussions and problem-solving. This volume clearly benefits professionals, academicians, data analysts, machine-learning community, undergraduate and postgraduate students.