Xinyue Ye – författare
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The rise of cloud computing and Generative artificial intelligence (AI) has revolutionized data analytics pipelines. Analysts can collect, store, and process vast datasets in the cloud with high availability and scalability, and also leverage Generative AI to query and visualize datasets in natural languages. This pioneering textbook provides a gateway for students, educators, and professionals to develop and enhance social data analytics capabilities with the latest cloud computing and AI technologies. The textbook introduces educational cloud resources from leading technology companies, begins with foundational concepts, and progresses to advanced techniques.
Features
The first textbook on cloud-based social data analytics with the assistance of Generative AI. Introduces educational cloud resources from leading technology companies like AWS, GitHub, and MongoDB. Presents a fully AI-powered data analytics pipeline from Python coding to data collection with APIs, cloud-based data storage, natural language queries, and interactive visualization. Analyzes Census and social media data with the latest large language models (LLMs). Provides hands-on exercises with real-world datasets on timely issues.This textbook is an excellent resource for upper-level undergraduate and graduate students taking GIS, Urban Informatics, Social Science Data Analysis, and Data Science courses; faculty members teaching such courses; and professionals and researchers interested in leveraging cloud computing and Generative AI in social data analytics.
1 293 kr
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The rise of cloud computing and Generative artificial intelligence (AI) has revolutionized data analytics pipelines. Analysts can collect, store, and process vast datasets in the cloud with high availability and scalability, and also leverage Generative AI to query and visualize datasets in natural languages. This pioneering textbook provides a gateway for students, educators, and professionals to develop and enhance social data analytics capabilities with the latest cloud computing and AI technologies. The textbook introduces educational cloud resources from leading technology companies, begins with foundational concepts, and progresses to advanced techniques.
Features
The first textbook on cloud-based social data analytics with the assistance of Generative AI. Introduces educational cloud resources from leading technology companies like AWS, GitHub, and MongoDB. Presents a fully AI-powered data analytics pipeline from Python coding to data collection with APIs, cloud-based data storage, natural language queries, and interactive visualization. Analyzes Census and social media data with the latest large language models (LLMs). Provides hands-on exercises with real-world datasets on timely issues.This textbook is an excellent resource for upper-level undergraduate and graduate students taking GIS, Urban Informatics, Social Science Data Analysis, and Data Science courses; faculty members teaching such courses; and professionals and researchers interested in leveraging cloud computing and Generative AI in social data analytics.
2 596 kr
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This comprehensive handbook covers human mobility within urban contexts, integrating academic theories with pragmatic insights and offering a detailed analysis of the diverse facets of human mobility and its substantial impact on the urban landscape, economy, and societal structures. It explains key fundamental concepts, methods, and models, presenting an in-depth exploration of predictive analytics, clustering patterns, advanced trajectory embedding techniques, artificial intelligence, machine learning, geographic information systems (GIS), Internet of Things (IoT), and smart city innovations. The authors include many case studies and examples of urban mobility in practice, making the content relatable and practical for educators, students, researchers, and practitioners.
Features
Provides a multidisciplinary and holistic understanding of urban mobility with systematic introductions and discussions of theory, methods, technologies, tools, and applications. Covers a wide range of real-world case studies of urban mobility in practice globally that include data, programming code, and tools. Discusses cutting-edge technologies involved in mobility data analytics. Addresses practical challenges in data collection and the ethical implications of mobility research, which are crucial for professionals in the field. Offers future directions of human mobility research under the big data and artificial intelligence (AI) revolution.Urban Human Mobility: Practices, Analytics, and Strategies for Smart Cities is for professionals, academics, and upper-level undergraduate and graduate students in the fields of urban planning/design, GIScience, data mining, and social sciences.
2 596 kr
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This comprehensive handbook covers human mobility within urban contexts, integrating academic theories with pragmatic insights and offering a detailed analysis of the diverse facets of human mobility and its substantial impact on the urban landscape, economy, and societal structures. It explains key fundamental concepts, methods, and models, presenting an in-depth exploration of predictive analytics, clustering patterns, advanced trajectory embedding techniques, artificial intelligence, machine learning, geographic information systems (GIS), Internet of Things (IoT), and smart city innovations. The authors include many case studies and examples of urban mobility in practice, making the content relatable and practical for educators, students, researchers, and practitioners.
Features
Provides a multidisciplinary and holistic understanding of urban mobility with systematic introductions and discussions of theory, methods, technologies, tools, and applications. Covers a wide range of real-world case studies of urban mobility in practice globally that include data, programming code, and tools. Discusses cutting-edge technologies involved in mobility data analytics. Addresses practical challenges in data collection and the ethical implications of mobility research, which are crucial for professionals in the field. Offers future directions of human mobility research under the big data and artificial intelligence (AI) revolution.Urban Human Mobility: Practices, Analytics, and Strategies for Smart Cities is for professionals, academics, and upper-level undergraduate and graduate students in the fields of urban planning/design, GIScience, data mining, and social sciences.
1 090 kr
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548 kr
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687 kr
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This book describes how powerful computing technology, emerging big and open data sources, and theoretical perspectives on spatial synthesis have revolutionized the way in which we investigate social sciences and humanities. It summarizes the principles and applications of human-centered computing and spatial social science and humanities research, thereby providing fundamental information that will help shape future research. The book illustrates how big spatiotemporal socioeconomic data facilitate the modelling of individuals’ economic behavior in space and time and how the outcomes of such models can reveal information about economic trends across spatial scales. It describes how spatial social science and humanities research has shifted from a data-scarce to a data-rich environment. The chapters also describe how a powerful analytical framework for identifying space-time research gaps and frontiers is fundamental to comparative study of spatiotemporal phenomena, and how research topics have evolved from structure and function to dynamic and predictive. As such this book provides an interesting read for researchers, students and all those interested in computational and spatial social sciences and humanities.
548 kr
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1 998 kr
Kommande
1 090 kr
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1 379 kr
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This book reports on the latest, cutting-edge scholarship on integrating social network and spatial analyses in the built environment. It sheds light on conceptualization and Implementation of such integration, integration for intra-city level analysis, as well as integration for inter-city level analysis. It explores the use of new data sources concerning human and urban dynamics and provides a discussion of how social network and spatial analyses could be synthesized for a more nuanced understanding of the built environment. As such this book will be a valuable resource for scholars focusing on city-related networks in a number of ‘urban’ disciplines, including but not limited to urban geography, urban informatics, urban planning, urban sociology, and urban studies.