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Data Driven Decision Making using Analytics

By: (Edited by) Kapal Dev , (Edited by) Parul Gandhi , (Edited by) Surbhi Bhatia

Manufacture on Demand

Ksh 8,000.00

Format: Paperback or Softback

ISBN-10: 1032058285

ISBN-13: 9781032058283

Series: Computational Intelligence Techniques

Publisher: Taylor & Francis Ltd

Imprint: CRC Press

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Oct 7th, 2024

Print length: 138 Pages

Weight: 240 grams

Product Classification: Data analysis: general
Decision theory: general
Management decision making
Electrical engineering
Electronics engineering

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This book aims to build and prompt the field of Data Analytics towards decision making in terms of models and algorithms, theoretical concepts, applications, experiments in relevant domains or focussed on specific issues, including concepts of Database Technology, Machine learning, Knowledge-based system, High Performance Computing etc.

This book aims to explain Data Analytics towards decision making in terms of models and algorithms, theoretical concepts, applications, experiments in relevant domains or focused on specific issues. It explores the concepts of database technology, machine learning, knowledge-based system, high performance computing, information retrieval, finding patterns hidden in large datasets and data visualization. Also, it presents various paradigms including pattern mining, clustering, classification, and data analysis. Overall aim is to provide technical solutions in the field of data analytics and data mining.

Features:

  • Covers descriptive statistics with respect to predictive analytics and business analytics.

  • Discusses different data analytics platforms for real-time applications.

  • Explain SMART business models.

  • Includes algorithms in data sciences alongwith automated methods and models.

  • Explores varied challenges encountered by researchers and businesses in the realm of real-time analytics.

This book aims at researchers and graduate students in data analytics, data sciences, data mining, and signal processing.

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