Anindya S.Chakrabarti,K. ShuvoBakar,AnirbanChakraborti
Data Science for Complex Systems
Data Science for Complex Systems
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The study of complex systems involves analysis and interpretation of vast quantities of data, requiring the application of classical and modern tools and techniques from statistics, network science, machine learning, and agent-based modelling. This self-contained and pedagogical text provides an accessible guide to a data-driven toolkit for scientists, engineers, and social scientists.
Format: Hardback
Length: 289 pages
Publication date: 25 May 2023
Publisher: Cambridge University Press
Complex systems are dynamic, evolving, and interconnected, encompassing a wide range of real-life domains. From economics to biology, the environment, and physical sciences, examples of complexity can be observed. The study of complex systems involves analyzing and interpreting vast amounts of data, requiring the application of various classical and modern tools and techniques from statistics, network science, machine learning, and agent-based modeling. This self-contained and pedagogical text explores some of the most important and widely used methods, emphasizing both empirical and theoretical approaches. Furthermore, this book serves as an accessible guide to a data-driven toolkit for scientists, engineers, and social scientists who need to effectively analyze large quantities of data, whether related to social networks, financial markets, economies, or other complex systems.
Complex systems are dynamic, evolving, and interconnected, encompassing a wide range of real-life domains. From economics to biology, the environment, and physical sciences, examples of complexity can be observed. The study of complex systems involves analyzing and interpreting vast amounts of data, requiring the application of various classical and modern tools and techniques from statistics, network science, machine learning, and agent-based modeling. This self-contained and pedagogical text explores some of the most important and widely used methods, emphasizing both empirical and theoretical approaches. Furthermore, this book serves as an accessible guide to a data-driven toolkit for scientists, engineers, and social scientists who need to effectively analyze large quantities of data, whether related to social networks, financial markets, economies, or other complex systems.
Complex systems are dynamic, evolving, and interconnected, encompassing a wide range of real-life domains. From economics to biology, the environment, and physical sciences, examples of complexity can be observed. The study of complex systems involves analyzing and interpreting vast amounts of data, requiring the application of various classical and modern tools and techniques from statistics, network science, machine learning, and agent-based modeling. This self-contained and pedagogical text explores some of the most important and widely used methods, emphasizing both empirical and theoretical approaches. Furthermore, this book serves as an accessible guide to a data-driven toolkit for scientists, engineers, and social scientists who need to effectively analyze large quantities of data, whether related to social networks, financial markets, economies, or other complex systems.
Weight: 696g
Dimension: 177 x 252 x 24 (mm)
ISBN-13: 9781108844796
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