000			01708nam a22002177a 4500
005			20241216191709.0
008			241216b |||||||| |||| 00| 0 eng d
020			_a9781108844796
082			_a006.3 _bCHA
100			_aChakrabarti, Anindya S _919699
245			_aData science for complex systems
260			_bCambridge University Press _aNew York _c2023
300			_ax, 293 p.
365			_aGBP _b54.99
520			_aMany real-life systems are dynamic, evolving, and intertwined. Examples of such systems displaying 'complexity', can be found in a wide variety of contexts ranging from economics to biology, to the environmental and physical sciences. The study of complex systems involves analysis and interpretation of vast quantities of data, which necessitates the application of many classical and modern tools and techniques from statistics, network science, machine learning, and agent-based modelling. Drawing from the latest research, this self-contained and pedagogical text describes some of the most important and widely used methods, emphasising both empirical and theoretical approaches. More broadly, this book provides an accessible guide to a data-driven toolkit for scientists, engineers, and social scientists who require effective analysis of large quantities of data, whether that be related to social networks, financial markets, economies or other types of complex systems. (https://www.cambridge.org/core/books/data-science-for-complex-systems/304F66053C62CD439FDFA46D2D4323A8#fndtn-information)
650			_aData mining
650			_aSystem theory--Data processing _919700
700			_aBakar, Shuvo K _919701
700			_aChakraborti, Anirban _919702
942			_cBK _2ddc
999			_c7655 _d7655