9783031830969 - informed machine learning (cognitive technologies) (12 resultados)
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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EUR 66,89
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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EUR 61,30
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 80,91
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 90,06
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Hardcover. Condición: Brand New. 352 pages. 9.25x6.10x9.21 inches. In Stock.
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Idioma: Inglés
Editorial: Springer Nature Switzerland, Springer Nature Switzerland, 2025
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 53,49
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This open access book presents the concept of Informed Machine Learning and demonstrates its practical use with a compelling collection of applications of this paradigm in industrial and business use cases. These range from health care over manufacturing…and material science to more advanced combinations with deep learning, say, in the form of physical informed neural networks. The book is intended for those interested in modern informed machine learning for a wide range of practical applicationswhere the aspect of small data sets is a challenge.Machine Learning with small amounts of data After the recent success of Artificial Intelligence based on training with massive amounts of data, this idea may sound exotic. However, it addresses crucial needs of practitioners in industry. While many industrial applications stand to benefit from the use of AI, the amounts of data needed by current learning paradigms are often hard to come by in industrial settings. As an alternative, learning methods and models are called for which integrate other sources of knowledge in order to compensate for the lack of data. This is where the principle of 'Informed Machine Learning' comes into play.Informed Machine Learning combines purely data driven learning and knowledge-based techniques to learn from both data and knowledge. This has several advantages. It reduces the need for data, it often results in smaller, less complex and more robust models, and even makes machine learning applicable in settings where data is scarce. The kind of knowledge to be incorporated into learning processes can take many different forms, for example, differential equations, analytical models, simulation results, logical rules, knowledge graphs, or human feedback which makes the approach overall very powerful and widely applicable.
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Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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EUR 46,22
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Condición: new. Questo è un articolo print on demand.
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Librería: Basi6 International, Irving, TX, Estados Unidos de AmericaBasi6 International
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EUR 61,79
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 10 disponibles
Condición: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days. Excellent Customer Service.
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Idioma: Inglés
Editorial: Springer Nature Switzerland, Springer Nature Switzerland Apr 2025, 2025
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 53,49
Envío por EUR 23,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This open access book presents the concept of Informed Machine Learning and demonstrates its practical use with a compelling collection of applications of this paradigm in industrial and business use cases. These range from health care ove…r manufacturing and material science to more advanced combinations with deep learning, say, in the form of physical informed neural networks. The book is intended for those interested in modern informed machine learning for a wide range of practical applicationswhere the aspect of small data sets is a challenge.Machine Learning with small amounts of data After the recent success of Artificial Intelligence based on training with massive amounts of data, this idea may sound exotic. However, it addresses crucial needs of practitioners in industry. While many industrial applications stand to benefit from the use of AI, the amounts of data needed by current learning paradigms are often hard to come by in industrial settings. As an alternative, learning methods and models are called for which integrate other sources of knowledge in order to compensate for the lack of data. This is where the principle of 'Informed Machine Learning' comes into play.Informed Machine Learning combines purely data driven learning and knowledge-based techniques to learn from both data and knowledge. This has several advantages. It reduces the need for data, it often results in smaller, less complex and more robust models, and even makes machine learning applicable in settings where data is scarce. The kind of knowledge to be incorporated into learning processes can take many different forms, for example, differential equations, analytical models, simulation results, logical rules, knowledge graphs, or human feedback which makes the approach overall very powerful and widely applicable. 356 pp. Englisch.
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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EUR 79,98
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Condición: New. Print on Demand.
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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EUR 79,39
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Condición: New. PRINT ON DEMAND.
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Librería: moluna, Greven, Alemaniamoluna
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EUR 48,37
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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EUR 53,49
Envío por EUR 60,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This open access book presents the concept of Informed Machine Learning and demonstrates its practical use with a compelling collection of applications of this paradigm in industrial and business use cases. These range from health care over ma…nufacturing and material science to more advanced combinations with deep learning, say, in the form of physical informed neural networks. The book is intended for those interested in modern informed machine learning for a wide range of practical applications where the aspect of small data sets is a challenge.Machine Learning with small amounts of data After the recent success of Artificial Intelligence based on training with massive amounts of data, this idea may sound exotic. However, it addresses crucial needs of practitioners in industry. While many industrial applications stand to benefit from the use of AI, the amounts of data needed by current learning paradigms are often hard to come by in industrial settings. As an alternative, learning methods and models are called for which integrate other sources of knowledge in order to compensate for the lack of data. This is where the principle of 'Informed Machine Learning' comes into play.Informed Machine Learning combines purely data driven learning and knowledge-based techniques to learn from both data and knowledge. This has several advantages. It reduces the need for data, it often results in smaller, less complex and more robust models, and even makes machine learning applicable in settings where data is scarce. The kind of knowledge to be incorporated into learning processes can take many different forms, for example, differential equations, analytical models, simulation results, logical rules, knowledge graphs, or human feedback which makes the approach overall very powerful and widely applicable.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 356 pp. Englisch.
