- Table View
- List View
Genetic Programming: 27th European Conference, EuroGP 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3–5, 2024, Proceedings (Lecture Notes in Computer Science #14631)
by Mario Giacobini Bing Xue Luca ManzoniThis book constitutes the refereed proceedings of the 27th European Conference on Genetic Programming, EuroGP 2024, held in Aberystwyth, UK, April 3–5, 2024 and co-located with the EvoStar events, EvoCOP, EvoMUSART, and EvoApplications.The 13 papers (9 selected for long presentation and 4 for short presentation) collected in this book were carefully reviewed and selected from 24 submissions. The wide range of topics in this volume reflects the current state of research in the field. The collection of papers cover topics including developing new variants of GP algorithms, as well as exploring GP applications to the optimization of machine learning methods and the evolution of control policies.
Data Visualization for People of All Ages (ISSN)
by Nancy OrganData visualization is the art and science of making information visible. On paper and in our imaginations, it’s a language of shapes and colors that holds our best ideas and most important questions. As we find ourselves swimming in data of all kinds, visualization can help us to understand, express, and explore the richness of the world around us. No matter your age or background, this book opens the door to new ways of thinking and sharing through the power of data visualization.Data Visualization for People of All Ages is a field guide to visual literacy, born from the author’s personal experience working with world-class scholars, engineers, and scientists. By walking through the different ways of showing data—including color, angle, position, and length—you’ll learn how charts and graphs truly work so that no visualization is ever a mystery or out of reach. It doesn’t stop at what fits on a page, either. You’ll journey into cutting-edge topics like data sonification and data physicalization, using sound and touch to share data across the different senses. Packed with practical examples and exercises to help you connect the dots, this book will teach you how to create and understand data visualizations on your own—all without writing a single line of code or getting tangled up in software.Written with accessibility in mind, this book invites everyone to the table to share the joy of one of today’s most necessary skills. Perfect for home or classroom use, this friendly companion gives people of all ages everything they need to start visualizing with confidence.
Data Visualization for People of All Ages (ISSN)
by Nancy OrganData visualization is the art and science of making information visible. On paper and in our imaginations, it’s a language of shapes and colors that holds our best ideas and most important questions. As we find ourselves swimming in data of all kinds, visualization can help us to understand, express, and explore the richness of the world around us. No matter your age or background, this book opens the door to new ways of thinking and sharing through the power of data visualization.Data Visualization for People of All Ages is a field guide to visual literacy, born from the author’s personal experience working with world-class scholars, engineers, and scientists. By walking through the different ways of showing data—including color, angle, position, and length—you’ll learn how charts and graphs truly work so that no visualization is ever a mystery or out of reach. It doesn’t stop at what fits on a page, either. You’ll journey into cutting-edge topics like data sonification and data physicalization, using sound and touch to share data across the different senses. Packed with practical examples and exercises to help you connect the dots, this book will teach you how to create and understand data visualizations on your own—all without writing a single line of code or getting tangled up in software.Written with accessibility in mind, this book invites everyone to the table to share the joy of one of today’s most necessary skills. Perfect for home or classroom use, this friendly companion gives people of all ages everything they need to start visualizing with confidence.
Measure of Noncompactness, Fixed Point Theorems, and Applications
by S. A. Mohiuddine M. Mursaleen Dragan S. DjordjevićThe theory of the measure of noncompactness has proved its significance in various contexts, particularly in the study of fixed point theory, differential equations, functional equations, integral and integrodifferential equations, optimization, and others. This edited volume presents the recent developments in the theory of the measure of noncompactness and its applications in pure and applied mathematics. It discusses important topics such as measures of noncompactness in the space of regulated functions, application in nonlinear infinite systems of fractional differential equations, and coupled fixed point theorem.Key Highlights: Explains numerical solution of functional integral equation through coupled fixed point theorem, measure of noncompactness and iterative algorithm Showcases applications of the measure of noncompactness and Petryshyn’s fixed point theorem functional integral equations in Banach algebra Explores the existence of solutions of the implicit fractional integral equation via extension of the Darbo’s fixed point theorem Discusses best proximity point results using measure of noncompactness and its applications Includes solvability of some fractional differential equations in the holder space and their numerical treatment via measures of noncompactness This reference work is for scholars and academic researchers in pure and applied mathematics.
Measure of Noncompactness, Fixed Point Theorems, and Applications
The theory of the measure of noncompactness has proved its significance in various contexts, particularly in the study of fixed point theory, differential equations, functional equations, integral and integrodifferential equations, optimization, and others. This edited volume presents the recent developments in the theory of the measure of noncompactness and its applications in pure and applied mathematics. It discusses important topics such as measures of noncompactness in the space of regulated functions, application in nonlinear infinite systems of fractional differential equations, and coupled fixed point theorem.Key Highlights: Explains numerical solution of functional integral equation through coupled fixed point theorem, measure of noncompactness and iterative algorithm Showcases applications of the measure of noncompactness and Petryshyn’s fixed point theorem functional integral equations in Banach algebra Explores the existence of solutions of the implicit fractional integral equation via extension of the Darbo’s fixed point theorem Discusses best proximity point results using measure of noncompactness and its applications Includes solvability of some fractional differential equations in the holder space and their numerical treatment via measures of noncompactness This reference work is for scholars and academic researchers in pure and applied mathematics.
Recent Trends in AI Enabled Technologies: First International Conference, ThinkAI 2023, Hyderabad, India, December 29, 2023, Revised Selected Papers (Communications in Computer and Information Science #2045)
by Gangamohan Paidi Suryakanth V Gangashetty Ashwini Kumar VarmaThis book constitutes the refereed proceedings of the First International Conference on Recent Trends in AI Enabled Technologies, ThinkAI 2023, which took place in Hyderabad, India, in December 2023. The 7 full papers presented in these proceedings were carefully reviewed and selected from 51 submissions. The conference focuses on on up to date topics and recent trends in artificial intelligence and related technologies.
New Perspectives and Paradigms in Applied Economics and Business: Select Proceedings of the 7th International Conference on Applied Economics and Business, Copenhagen, Denmark, 2023 (Springer Proceedings in Business and Economics)
by William C. GartnerThis book features a collection of high-quality and peer-reviewed papers from the 2023 7th International Conference on Applied Economics and Business, which was held in Copenhagen, Denmark, during August 24-26, 2023. ICAEB is held annually as a platform for the presentation of new advances and research results in the fields of applied economics and business. Applied economics is a way of dealing with esoteric economic concepts in a practical and analytical way. It allows for decisions to be made that are underlined by theoretical economic principles but utilized in such a way that they transform into real work applications.The contributors cover topics such as environment, development, finance, forensics, information, institutions, international, labor, management, mathematics, currency, tourism and many more. Applied Economics affects all aspects of life and science and it is brought to the forefront in this collection of papers. The conference, with its aim to bring together economists from different fields, lends itself to a natural and rich collection of scientific papers all focused on the practical application of economic principles. The scope of this collection of papers will be useful to academics and practitioners who look to economics to help solve problems.
Methodenvorschlag zur Berechnung der Sonneneinstrahlung für Prognosen: Mathematische Verfahren für die ingenieurtechnische Anwendung
by Larissa HilleUm eine effiziente Nutzung erneuerbarer Energien zu ermöglichen, werden zuverlässige Prognosen für die Intensität der Sonneneinstrahlung benötigt. Im ersten Teil dieses Buchs wird eine neue, effiziente Methode für die Berechnung der diffusen Strahlung vorgestellt. Sie bestimmt die Intensität des gestreuten Lichts in einer Umgebung mit einer vertikal und horizontal variierenden Anzahldichte der streuenden Partikel. Die Methode kombiniert Monte-Carlo-Simulationen mit der Integralrechnung. Sie ermöglicht das Wiederverwenden berechneter Ergebnisse und erfordert bei einer vielfachen Anwendung einen geringen Rechenaufwand. Im zweiten Teil dieses Buchs wird eine einfache und genaue Methode zur Berechnung der Sonnenposition beschrieben. Die Methode basiert auf dem zweiten Keplerschen Gesetz und verwendet eine exakte trigonometrische Formel für die Fläche eines Ellipsensektors.
Solutions of Fixed Point Problems with Computational Errors (Springer Optimization and Its Applications #210)
by Alexander J. ZaslavskiThe book is devoted to the study of approximate solutions of fixed point problems in the presence of computational errors. It begins with a study of approximate solutions of star-shaped feasibility problems in the presence of perturbations. The goal is to show the convergence of algorithms, which are known as important tools for solving convex feasibility problems and common fixed point problems.The text also presents studies of algorithms based on unions of nonexpansive maps, inconsistent convex feasibility problems, and split common fixed point problems. A number of algorithms are considered for solving convex feasibility problems and common fixed point problems. The book will be of interest for researchers and engineers working in optimization, numerical analysis, and fixed point theory. It also can be useful in preparation courses for graduate students. The main feature of the book which appeals specifically to this audience is the study of the influence of computational errorsfor several important algorithms used for nonconvex feasibility problems.
Everything Is Predictable: How Bayes' Remarkable Theorem Explains the World
by Tom ChiversThomas Bayes was an eighteenth-century Presbyterian minister and amateur mathematician whose obscure life belied the profound impact of his work. Like most research into probability at the time, his theorem was mainly seen as relevant to games of chance, like dice and cards. But its implications soon became clear. Bayes' theorem helps explain why highly accurate screening tests can lead to false positives, causing unnecessary anxiety for patients. A failure to account for it in court has put innocent people in jail. But its influence goes far beyond practical applications. A cornerstone of rational thought, Bayesian principles are used in modelling and forecasting. 'Superforecasters', a group of expert predictors who outperform CIA analysts, use a Bayesian approach. And many argue that Bayes' theorem is not just a useful tool, but a description of almost everything - that it is the underlying architecture of rationality, and of the human brain. Fusing biography, razor-sharp science communication and intellectual history, Everything Is Predictable is a captivating tour of Bayes' theorem and its impact on modern life. From medical testing to artificial intelligence, Tom Chivers shows how a single compelling idea can have far-reaching consequences.
From Concepts to Code: Introduction to Data Science
by Adam P. TashmanThe breadth of problems that can be solved with data science is astonishing, and this book provides the required tools and skills fot a broad audience. The reader takes a journey into the forms, uses, and abuses of data and models, and learns how to critically examine each step. Python coding and data analysis skills are built from the ground up, with no prior coding experience assumed. The necessary background in computer science, mathematics, and statistics is provided in an approachable manner.Each step of the machine learning lifecycle is discussed, from business objective planning to monitoring a model in production. This end-to-end approach supplies the broad view necessary to sidestep many of the pitfalls that can sink a data science project. Detailed examples are provided from a wide range of applications and fields, from fraud detection in banking to breast cancer classification in healthcare. The reader will learn the techniques to accomplish tasks that include predicting outcomes, explaining observations, and detecting patterns. Improper use of data and models can introduce unwanted effects and dangers to society. A chapter on model risk provides a framework for comprehensively challenging a model and mitigating weaknesses. When data is collected, stored, and used, it may misrepresent reality and introduce bias. Strategies for addressing bias are discussed. From Concepts to Code: Introduction to Data Science leverages content developed by the author for a full-year data science course suitable for advanced high school or early undergraduate students. This course is freely available and it includes weekly lesson plans.
From Concepts to Code: Introduction to Data Science
by Adam P. TashmanThe breadth of problems that can be solved with data science is astonishing, and this book provides the required tools and skills fot a broad audience. The reader takes a journey into the forms, uses, and abuses of data and models, and learns how to critically examine each step. Python coding and data analysis skills are built from the ground up, with no prior coding experience assumed. The necessary background in computer science, mathematics, and statistics is provided in an approachable manner.Each step of the machine learning lifecycle is discussed, from business objective planning to monitoring a model in production. This end-to-end approach supplies the broad view necessary to sidestep many of the pitfalls that can sink a data science project. Detailed examples are provided from a wide range of applications and fields, from fraud detection in banking to breast cancer classification in healthcare. The reader will learn the techniques to accomplish tasks that include predicting outcomes, explaining observations, and detecting patterns. Improper use of data and models can introduce unwanted effects and dangers to society. A chapter on model risk provides a framework for comprehensively challenging a model and mitigating weaknesses. When data is collected, stored, and used, it may misrepresent reality and introduce bias. Strategies for addressing bias are discussed. From Concepts to Code: Introduction to Data Science leverages content developed by the author for a full-year data science course suitable for advanced high school or early undergraduate students. This course is freely available and it includes weekly lesson plans.
Digital Forensics and Watermarking: 22nd International Workshop, IWDW 2023, Jinan, China, November 25–26, 2023, Revised Selected Papers (Lecture Notes in Computer Science #14511)
by Bin Ma Jian Li Qi LiThis book constitutes the refereed post proceedings of the 22nd International Workshop on Digital Forensics and Watermarking, IWDW 2023, held in Jinan, China, during November 25–26, 2023. The 22 full papers included in this book were carefully reviewed and selected from 48 submissions. The workshop focuses on subjects such as novel research, development and application of digital watermarking, data hiding, and forensic techniques for multimedia security.
Proceedings of the 2nd International Conference on Big Data, IoT and Machine Learning: BIM 2023 (Lecture Notes in Networks and Systems #867)
by Mohammad Shamsul Arefin M. Shamim Kaiser Touhid Bhuiyan Nilanjan Dey Mufti MahmudThis book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Big Data, IoT and Machine Learning (BIM 2023), organised by Jahangirnagar University, Bangladesh, and Daffodil International University, Bangladesh, held in Dhaka, Bangladesh, during 6–8 September 2023. The book covers research papers in the field of big data, IoT and machine learning. The book is helpful for active researchers and practitioners in the field.
Advances in Knowledge Discovery and Data Mining: 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7–10, 2024, Proceedings, Part III (Lecture Notes in Computer Science #14647)
by De-Nian Yang Xing Xie Vincent S. Tseng Jian Pei Jen-Wei Huang Jerry Chun-Wei LinThe 6-volume set LNAI 14645-14650 constitutes the proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, which took place in Taipei, Taiwan, during May 7–10, 2024. The 177 papers presented in these proceedings were carefully reviewed and selected from 720 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.
Math for Business and Economics: Compendium of Essential Formulas
by Franz W. PerenThis 3rd edition revised and extended compendium contains and explains essential mathematical formulas within an economic context. Newly added content introduces the mathematical practical application of optimization by using the Lagrange function, presenting the issue of linear optimization cases where the relative extremes (minima or maxima) of a linear (target) function can be determined under restrictive linear constraint and its relevance for business management practice. A broad range of aids and supportive examples will help readers to understand the formulas and their practical applications. This mathematical formulary is presented in a practice-oriented, clear, and understandable manner, as it is needed for meaningful and relevant application in global business, as well as in the academic setting and economic practice. The topics presented include but are not limited to mathematical signs and symbols, logic, arithmetic, algebra, linear algebra, combinatorics, and financial mathematics, including an international comparison between different national methods used in the calculation of interest, optimization of linear models, functions, differential calculus, integral calculus, elasticities, annuity calculation, economic functions, and the Peren Theorem.Given its scope, the book offers an indispensable reference guide and is a must-read for undergraduate and graduate students, as well as managers, scholars, and lecturers in business, politics, and economics.
Advances in Knowledge Discovery and Data Mining: 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7–10, 2024, Proceedings, Part I (Lecture Notes in Computer Science #14645)
by De-Nian Yang Xing Xie Vincent S. Tseng Jian Pei Jen-Wei Huang Jerry Chun-Wei LinThe 6-volume set LNAI 14645-14650 constitutes the proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, which took place in Taipei, Taiwan, during May 7–10, 2024. The 177 papers presented in these proceedings were carefully reviewed and selected from 720 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.
Operational Research: IO 2022—OR in Turbulent Times: Adaptation and Resilience. XXII Congress of APDIO, University of Évora, Portugal, November 6–8, 2022 (Springer Proceedings in Mathematics & Statistics #437)
by João Paulo Almeida Filipe Pereira e Alvelos Jorge Orestes Cerdeira Samuel Moniz Cristina RequejoThis book presents the XXII Congress of APDIO – IO 2022 which is the 22nd edition of the regular meeting of the Portuguese Association of Operational Research (APDIO). The APDIO regular meetings aim to gather Portuguese and international researchers, scholars and practitioners, as well as M.Sc. and Ph.D. students, working in the field of Operations Research to present and discuss their latest research works. The main theme of the XXII Congress of APDIO is OR in Turbulent Times: Adaptation and Resilience.Readers find interesting results and applications of Operational Research cutting-edge methods and techniques in the wide variety of the addressed problems. Of particular interest are the applications of, among others, linear, nonlinear and mixed-integer programing, multiobjective optimization, metaheuristics and hybrid heuristics, multicriteria decision analysis, data envelopment analysis, simulation, clustering techniques and decision support systems, in different areas such as, supply chain management, scheduling problems, production management, logistics, energy, telecommunications, finance and health.
Advances in Knowledge Discovery and Data Mining: 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7–10, 2024, Proceedings, Part V (Lecture Notes in Computer Science #14649)
by De-Nian Yang Xing Xie Vincent S. Tseng Jian Pei Jen-Wei Huang Jerry Chun-Wei LinThe 6-volume set LNAI 14645-14650 constitutes the proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, which took place in Taipei, Taiwan, during May 7–10, 2024. The 177 papers presented in these proceedings were carefully reviewed and selected from 720 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.
BRST Symmetry and de Rham Cohomology
by Soon-Tae HongThis book provides an advanced introduction to extended theories of quantum field theory and algebraic topology, including Hamiltonian quantization associated with some geometrical constraints, symplectic embedding and Hamilton-Jacobi quantization and Becchi-Rouet-Stora-Tyutin (BRST) symmetry, as well as de Rham cohomology. This extended new edition offers a multifaced insight into phenomenology of particles such as baryons and photons, in terms of extended objects. In particular, in the second edition, the baryons are described in hypersphere soliton model, and the photon properties are additionally included in stringy photon model and in Dirac type relativistic quantum mechanics for a photon.It offers a critical overview of the research in this area and unifies the existing literatures, employing a consistent notation. Although the results presented apply in principle to all alternative quantization schemes, special emphasis is placed on the BRST quantization and its de Rham cohomology group which contribute to a deep understanding of constrained physical theories. The book describes how solitons and other models subject to constraints include rigorous treatments of the geometrical constraints which affect the predictions themselves. The book is intended for use by any graduate-level student with quantum field and relativity theories, and it also serves as a useful reference for those working in the field. An extensive bibliography guides the reader toward the source literature on particular topics.
Advances in Knowledge Discovery and Data Mining: 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7–10, 2024, Proceedings, Part II (Lecture Notes in Computer Science #14646)
by De-Nian Yang Xing Xie Vincent S. Tseng Jian Pei Jen-Wei Huang Jerry Chun-Wei LinThe 6-volume set LNAI 14645-14650 constitutes the proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, which took place in Taipei, Taiwan, during May 7–10, 2024. The 177 papers presented in these proceedings were carefully reviewed and selected from 720 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.
Advances in Knowledge Discovery and Data Mining: 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7–10, 2024, Proceedings, Part VI (Lecture Notes in Computer Science #14650)
by De-Nian Yang Xing Xie Vincent S. Tseng Jian Pei Jen-Wei Huang Jerry Chun-Wei LinThe 6-volume set LNAI 14645-14650 constitutes the proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, which took place in Taipei, Taiwan, during May 7–10, 2024. The 177 papers presented in these proceedings were carefully reviewed and selected from 720 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.
Artificial Intelligence in Music, Sound, Art and Design: 13th International Conference, EvoMUSART 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3–5, 2024, Proceedings (Lecture Notes in Computer Science #14633)
by Colin Johnson Sérgio M. Rebelo Iria SantosThis book constitutes the refereed proceedings of the 13th International Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2024, held as part of EvoStar 2024, in Aberystwyth, UK, April 3–5, 2024. The 17 full papers and 8 short papers presented in this book were carefully reviewed and selected from 55 submissions. The main purpose of this conference proceedings was to bring together practitioners who are using Artificial Intelligence techniques for artistic tasks, providing the opportunity to promote, present, and discuss ongoing work in the area.
An Introduction to Spatial Data Science with GeoDa: Volume 1: Exploring Spatial Data
by Luc AnselinThis book is the first in a two-volume series that introduces the field of spatial data science. It offers an accessible overview of the methodology of exploratory spatial data analysis. It also constitutes the definitive user’s guide for the widely adopted GeoDa open-source software for spatial analysis. Leveraging a large number of real-world empirical illustrations, readers will gain an understanding of the main concepts and techniques, using dynamic graphics for thematic mapping, statistical graphing, and, most centrally, the analysis of spatial autocorrelation. Key to this analysis is the concept of local indicators of spatial association, pioneered by the author and recently extended to the analysis of multivariate data.The focus of the book is on intuitive methods to discover interesting patterns in spatial data. It offers a progression from basic data manipulation through description and exploration to the identification of clusters and outliers by means of local spatial autocorrelation analysis. A distinctive approach is to spatialize intrinsically non-spatial methods by means of linking and brushing with a range of map representations, including several that are unique to the GeoDa software. The book also represents the most in-depth treatment of local spatial autocorrelation and its visualization and interpretation by means of GeoDa.The book is intended for readers interested in going beyond simple mapping of geographical data to gain insight into interesting patterns. Some basic familiarity with statistical concepts is assumed, but no previous knowledge of GIS or mapping is required.Key Features:• Includes spatial perspectives on cluster analysis• Focuses on exploring spatial data• Supplemented by extensive support with sample data sets and examples on the GeoDaCenter websiteThis book is both useful as a reference for the software and as a text for students and researchers of spatial data science.Luc Anselin is the Founding Director of the Center for Spatial Data Science at the University of Chicago, where he is also the Stein-Freiler Distinguished Service Professor of Sociology and the College, as well as a member of the Committee on Data Science. He is the creator of the GeoDa software and an active contributor to the PySAL Python open-source software library for spatial analysis. He has written widely on topics dealing with the methodology of spatial data analysis, including his classic 1988 text on Spatial Econometrics. His work has been recognized by many awards, such as his election to the U.S. National Academy of Science and the American Academy of Arts and Science.
An Introduction to Spatial Data Science with GeoDa: Volume 1: Exploring Spatial Data
by Luc AnselinThis book is the first in a two-volume series that introduces the field of spatial data science. It offers an accessible overview of the methodology of exploratory spatial data analysis. It also constitutes the definitive user’s guide for the widely adopted GeoDa open-source software for spatial analysis. Leveraging a large number of real-world empirical illustrations, readers will gain an understanding of the main concepts and techniques, using dynamic graphics for thematic mapping, statistical graphing, and, most centrally, the analysis of spatial autocorrelation. Key to this analysis is the concept of local indicators of spatial association, pioneered by the author and recently extended to the analysis of multivariate data.The focus of the book is on intuitive methods to discover interesting patterns in spatial data. It offers a progression from basic data manipulation through description and exploration to the identification of clusters and outliers by means of local spatial autocorrelation analysis. A distinctive approach is to spatialize intrinsically non-spatial methods by means of linking and brushing with a range of map representations, including several that are unique to the GeoDa software. The book also represents the most in-depth treatment of local spatial autocorrelation and its visualization and interpretation by means of GeoDa.The book is intended for readers interested in going beyond simple mapping of geographical data to gain insight into interesting patterns. Some basic familiarity with statistical concepts is assumed, but no previous knowledge of GIS or mapping is required.Key Features:• Includes spatial perspectives on cluster analysis• Focuses on exploring spatial data• Supplemented by extensive support with sample data sets and examples on the GeoDaCenter websiteThis book is both useful as a reference for the software and as a text for students and researchers of spatial data science.Luc Anselin is the Founding Director of the Center for Spatial Data Science at the University of Chicago, where he is also the Stein-Freiler Distinguished Service Professor of Sociology and the College, as well as a member of the Committee on Data Science. He is the creator of the GeoDa software and an active contributor to the PySAL Python open-source software library for spatial analysis. He has written widely on topics dealing with the methodology of spatial data analysis, including his classic 1988 text on Spatial Econometrics. His work has been recognized by many awards, such as his election to the U.S. National Academy of Science and the American Academy of Arts and Science.