This text provides an accessible guide to the tools and techniques of data science that can be utilised for the analysis of complex systems. This text is an invaluable resource for scientists, engineers and social scientists who require effective analysis of large quantities of data.
Inhaltsverzeichnis
Preface; Part I. Introduction: 1. Facets of complex systems; Part II. Heterogeneity and Dependence: 2. Quantifying heterogeneity: Classical and Bayesian statistics; 3. Statistical analyses of time-varying phenomena; Part III. Patterns and Interlinkages: 4. Pattern recognition in complex systems: machine learning; 5. Interlinkages and heterogeneity: network theory. Part IV. Emergence: from Micros to Macro: 6. Interaction and emergence: agent-based models; 7. Epilogue; References; Index.
