9781032821177 - intersection of machine learning and computational social sciences (future generation information systems) (7 resultados)
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Librería: Majestic Books, Hounslow, , Reino UnidoMajestic Books
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EUR 228,99
Envío por EUR 7,53Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 3 disponibles
Condición: New.
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 258,19
Envío por EUR 3,45Se envía dentro de Estados Unidos de AmericaCantidad disponible: 3 disponibles
Condición: New.
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Librería: moluna, Greven, , Alemaniamoluna
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EUR 210,93
Envío por EUR 48,99Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New.
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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EUR 255,70
Envío por EUR 9,95Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 3 disponibles
Condición: New.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 260,19
Envío por EUR 64,20Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Buch. Condición: Neu. Neuware - The text employs computational techniques and large-scale data analysis to study complex social phenomena and human behavior. It discusses diverse methodologies, including agent-based modeling, network analysis, natural language processing, and machine learning, to gain insights into topics rangin…g from social network dynamics and opinion formation to economic trends and public health crises.Features: - Discusses the theoretical background of each algorithm in detail and presents the applications of each method. - Presents artificial intelligence implications, sustainable artificial intelligence, and the importance of artificial intelligence in agriculture, and energy. - Explains the use of predictive modeling in computational social science and applications of computational social science. - Showcases the framework for social network analysis, application program interface, data collection methods, and data preprocessing. - Covers topics such as density-based spatial clustering of applications with noise, the role of clustering in computational social science, and clustering in network structure. The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 236,71
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: new. Hardcover. The text employs computational techniques and large-scale data analysis to study complex social phenomena and human behavior. It discusses diverse methodologies, including agent-based modeling, network analysis, natural language processing, and machine learning, to gain insights into topics…ranging from social network dynamics and opinion formation to economic trends and public health crises.Features:Discusses the theoretical background of each algorithm in detail and presents the applications of each method.Presents artificial intelligence implications, sustainable artificial intelligence, and the importance of artificial intelligence in agriculture, and energy.Explains the use of predictive modeling in computational social science and applications of computational social science.Showcases the framework for social network analysis, application program interface, data collection methods, and data preprocessing.Covers topics such as density-based spatial clustering of applications with noise, the role of clustering in computational social science, and clustering in network structure.The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology. The text discusses theoretical background of algorithms and applications of methods using social science problems. It explores different machine-learning approaches to tackle the current issues in the digital world by analyzing social networks. It discusses topics such as principles of semi-supervised learning, and reinforcement algorithms. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 261,99
Envío por EUR 42,88Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: new. Hardcover. The text employs computational techniques and large-scale data analysis to study complex social phenomena and human behavior. It discusses diverse methodologies, including agent-based modeling, network analysis, natural language processing, and machine learning, to gain insights into topics…ranging from social network dynamics and opinion formation to economic trends and public health crises.Discusses the theoretical background of each algorithm in detail and presents the applications of each method.Presents artificial intelligence implications, sustainable artificial intelligence, and the importance of artificial intelligence in agriculture, and energy.Explains the use of predictive modeling in computational social science and applications of computational social science.Showcases the framework for social network analysis, application program interface, data collection methods, and data preprocessing.Covers topics such as density-based spatial clustering of applications with noise, the role of clustering in computational social science, and clustering in network structure.The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology. The text discusses theoretical background of algorithms and applications of methods using social science problems. It explores different machine-learning approaches to tackle the current issues in the digital world by analyzing social networks. It discusses topics such as principles of semi-supervised learning, and reinforcement algorithms. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
