Applied graph data science (17 resultados)
Idioma: Inglés
Editorial: Orange Education Pvt Ltd 2024
Serie: Graph & Big Data Analytics — Applied Path, Libro 1 de 2. Libro 1 de 2 - Graph & Big Data Analytics — Applied Path
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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EUR 38,10
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Condición: New.
Idioma: Inglés
Editorial: Orange Education Pvt Ltd 2024
Serie: Graph & Big Data Analytics — Applied Path, Libro 1 de 2. Libro 1 de 2 - Graph & Big Data Analytics — Applied Path
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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EUR 37,74
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Condición: New. In.
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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EUR 167,99
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Applied Graph Data Science : Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks and Applied Use Cases
Raj, Pethuru (EDT); Dutta, Pushan Kumar (EDT); Chong, Peter Han Joo (EDT); Song, Houbing Herbert (EDT); Zaitsev, Dmitry A. (EDT)
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 192,31
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Condición: New.
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 191,09
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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EUR 192,02
Envío por EUR 9,95Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 3 disponibles
Condición: New.
Idioma: Inglés
Editorial: Elsevier Science & Technology, San Francisco 2025
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Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
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EUR 168,37
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Paperback. Condición: new. Paperback. Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Use Cases delineates how graph data science significantly empowers the application of data science. The book discusses the emerging paradigm of graph data science in detail along with i…ts practical research and real-world applications. Readers will be enriched with the knowledge of graph data science, graph analytics, algorithms, databases, platforms, and use cases across a variety of research and topics and applications. This book also presents how graphs are used as a programming language, especially demonstrating how Sleptsov Net Computing can contribute as an entirely graphical concurrent processing language for supercomputers. Graph data science is emerging as an expressive and illustrative data structure for optimally representing a variety of data types and their insightful relationships. These data structures include graph query languages, databases, algorithms, and platforms. From here, powerful analytics methods and machine learning/deep learning (ML/DL) algorithms are quickly evolving to analyze and make sense out of graph data. As a result, ground-breaking use cases across scientific research topics and industry verticals are being developed using graph data representation and manipulation. A wide range of complex business and scientific research requirements are efficiently represented and solved through graph data analysis, and Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Graph Data Science gives readers both the conceptual foundations and technical methods for applying these powerful techniques. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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EUR 200,99
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Condición: New. In.
Applied Graph Data Science : Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks and Applied Use Cases
Raj, Pethuru (EDT); Dutta, Pushan Kumar (EDT); Chong, Peter Han Joo (EDT); Song, Houbing Herbert (EDT); Zaitsev, Dmitry A. (EDT)
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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EUR 200,98
Envío por EUR 17,39Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New.
Applied Graph Data Science : Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks and Applied Use Cases
Raj, Pethuru (EDT); Dutta, Pushan Kumar (EDT); Chong, Peter Han Joo (EDT); Song, Houbing Herbert (EDT); Zaitsev, Dmitry A. (EDT)
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 226,31
Envío por EUR 2,33Se envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: As New. Unread book in perfect condition.
Applied Graph Data Science : Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks and Applied Use Cases
Raj, Pethuru (EDT); Dutta, Pushan Kumar (EDT); Chong, Peter Han Joo (EDT); Song, Houbing Herbert (EDT); Zaitsev, Dmitry A. (EDT)
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Como Nuevo
EUR 224,28
Envío por EUR 17,39Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: As New. Unread book in perfect condition.
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Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA
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EUR 248,60
Gastos de envío gratisSe envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Paperback. Condición: New. Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Use Cases delineates how graph data science significantly empowers the application of data science. The book discusses the emerging paradigm of graph data science in detail along with its practica…l research and real-world applications. Readers will be enriched with the knowledge of graph data science, graph analytics, algorithms, databases, platforms, and use cases across a variety of research and topics and applications. This book also presents how graphs are used as a programming language, especially demonstrating how Sleptsov Net Computing can contribute as an entirely graphical concurrent processing language for supercomputers. Graph data science is emerging as an expressive and illustrative data structure for optimally representing a variety of data types and their insightful relationships. These data structures include graph query languages, databases, algorithms, and platforms. From here, powerful analytics methods and machine learning/deep learning (ML/DL) algorithms are quickly evolving to analyze and make sense out of graph data. As a result, ground-breaking use cases across scientific research topics and industry verticals are being developed using graph data representation and manipulation. A wide range of complex business and scientific research requirements are efficiently represented and solved through graph data analysis, and Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Graph Data Science gives readers both the conceptual foundations and technical methods for applying these powerful techniques.
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Librería: moluna, Greven, Alemaniamoluna
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EUR 205,63
Envío por EUR 48,99Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New. Provides comprehensive coverage of the emerging paradigm of graph data science and its real-world applicationsGives readers practical guidance on how to approach and solve complex data analysis problems using graph data science, with an emp.
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Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 234,98
Envío por EUR 75,36Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Paperback. Condición: New. Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Use Cases delineates how graph data science significantly empowers the application of data science. The book discusses the emerging paradigm of graph data science in detail along with its practica…l research and real-world applications. Readers will be enriched with the knowledge of graph data science, graph analytics, algorithms, databases, platforms, and use cases across a variety of research and topics and applications. This book also presents how graphs are used as a programming language, especially demonstrating how Sleptsov Net Computing can contribute as an entirely graphical concurrent processing language for supercomputers. Graph data science is emerging as an expressive and illustrative data structure for optimally representing a variety of data types and their insightful relationships. These data structures include graph query languages, databases, algorithms, and platforms. From here, powerful analytics methods and machine learning/deep learning (ML/DL) algorithms are quickly evolving to analyze and make sense out of graph data. As a result, ground-breaking use cases across scientific research topics and industry verticals are being developed using graph data representation and manipulation. A wide range of complex business and scientific research requirements are efficiently represented and solved through graph data analysis, and Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Graph Data Science gives readers both the conceptual foundations and technical methods for applying these powerful techniques.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 287,41
Envío por EUR 63,96Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Taschenbuch. Condición: Neu. Neuware - Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Use Cases delineates how graph data science significantly empowers the application of data science. The book discusses the emerging paradigm of graph data science in detail along with…its practical research and real-world applications. Readers will be enriched with the knowledge of graph data science, graph analytics, algorithms, databases, platforms, and use cases across a variety of research and topics and applications. This book also presents how graphs are used as a programming language, especially demonstrating how Sleptsov Net Computing can contribute as an entirely graphical concurrent processing language for supercomputers. Graph data science is emerging as an expressive and illustrative data structure for optimally representing a variety of data types and their insightful relationships. These data structures include graph query languages, databases, algorithms, and platforms. From here, powerful analytics methods and machine learning/deep learning (ML/DL) algorithms are quickly evolving to analyze and make sense out of graph data. As a result, ground-breaking use cases across scientific research topics and industry verticals are being developed using graph data representation and manipulation. A wide range of complex business and scientific research requirements are efficiently represented and solved through graph data analysis, and Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Graph Data Science gives readers both the conceptual foundations and technical methods for applying these powerful techniques.
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Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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EUR 148,78
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Condición: new. Questo è un articolo print on demand.
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 165,42
Envío por EUR 14,49Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Paperback. Condición: Brand New. 250 pages. 9.25x7.50x10.50 inches. In Stock. This item is printed on demand.
