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Destinos, gastos y plazos de envíoLibrería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
Condición: New. Nº de ref. del artículo: ABLING22Oct2817100110483
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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
HRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: L1-9781522590965
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Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: L1-9781522590965
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
Condición: New. In. Nº de ref. del artículo: ria9781522590965_new
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Librería: moluna, Greven, Alemania
Condición: New. KlappentextrnrnLink prediction is required to understand the evolutionary theory of computing for different social networks. However, the stochastic growth of the social network leads to various challenges in identifying hidden links, such as re. Nº de ref. del artículo: 448011631
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Link prediction is required to understand the evolutionary theory of computing for different social networks. However, the stochastic growth of the social network leads to various challenges in identifying hidden links, such as representation of graph, distinction between spurious and missing links, selection of link prediction techniques comprised of network features, and identification of network types. Hidden Link Prediction in Stochastic Social Networks concentrates on the foremost techniques of hidden link predictions in stochastic social networks including methods and approaches that involve similarity index techniques, matrix factorization, reinforcement, models, and graph representations and community detections. The book also includes miscellaneous methods of different modalities in deep learning, agent-driven AI techniques, and automata-driven systems and will improve the understanding and development of automated machine learning systems for supervised, unsupervised, and recommendation-driven learning systems. It is intended for use by data scientists, technology developers, professionals, students, and researchers. Nº de ref. del artículo: 9781522590965
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Librería: Revaluation Books, Exeter, Reino Unido
Hardcover. Condición: Brand New. 281 pages. 10.00x7.00x0.83 inches. In Stock. Nº de ref. del artículo: x-152259096X
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