Xin W. Chen
Network Science Models for Data Analytics Automation: Theories and Applications
Network Science Models for Data Analytics Automation: Theories and Applications
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- More about Network Science Models for Data Analytics Automation: Theories and Applications
This book provides a comprehensive introduction to network science and its applications in data analytics, bridging the gap between theory and practice. It is suitable for engineers, researchers, and managers, and advanced undergraduate and graduate students in mathematics, statistics, engineering, business, public health, and social science.
Format: Paperback / softback
Length: 122 pages
Publication date: 23 February 2023
Publisher: Springer Nature Switzerland AG
This comprehensive book delves into the realm of network science, providing a comprehensive understanding of its applications in data analytics for critical infrastructures, engineered systems, and knowledge acquisition. Spanning multiple chapters, it intricately outlines the step-by-step processes through which network science empowers and automates data analytics, offering practical examples along the way. Beyond dissecting modeling techniques and analytical outcomes, the book delves into the intrinsic development of these models and analyses, fostering a deep understanding of the underlying principles. By bridging the gap between theory and practice, this unique approach equips readers with managerial and problem-solving skills, making it invaluable for engineers, researchers, and managers alike.
Advanced undergraduate students and graduate students in mathematics, statistics, engineering, business, public health, and social science will find this book an indispensable resource for their studies. It serves as a one-semester textbook or a comprehensive reference book, offering a wealth of theoretical background and practical examples to enhance their understanding of network science and its applications.
For readers with a particular interest in applications, Chapter 1 can be skipped, allowing for a seamless exploration of the remaining chapters. Whether you are a seasoned professional seeking to expand your knowledge or a student embarking on a journey into the world of network science, this book is a valuable asset that will deepen your understanding and contribute to your success.
Weight: 209g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030964726
Edition number: 1st ed. 2022
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