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EUR 51,41
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Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
Da: Books Puddle, New York, NY, U.S.A.
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EUR 58,75
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Aggiungi al carrelloCondizione: New. pages cm First edition Includes bibliographical references and index.
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Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
Da: Majestic Books, Hounslow, Regno Unito
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EUR 57,64
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Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
Da: Ria Christie Collections, Uxbridge, Regno Unito
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EUR 57,96
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Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
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Prima edizione
EUR 66,10
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Aggiungi al carrelloCondizione: New. 2024. 1st Edition. paperback. . . . . .
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Knowledge Guided Machine Learning: Accelerating Discovery Using Scientific Knowledge and Data
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
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EUR 55,91
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Knowledge Guided Machine Learning : Accelerating Discovery Using Scientific Knowledge and Data
Da: GreatBookPrices, Columbia, MD, U.S.A.
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EUR 55,56
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EUR 63,54
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Aggiungi al carrelloCondizione: New. Anuj Karpatne is an Assistant Professor in the Department of Computer Science at Virginia Tech. His research focuses on pushing on the frontiers of knowledge-guided machine learning by combining scientific knowledge and data in the design and learning of.
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EUR 50,00
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Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data (Chapman & Hall/CRC Data Mining and Knowledge Discovery)
Da: Chiron Media, Wallingford, Regno Unito
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EUR 54,94
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Knowledge Guided Machine Learning: Accelerating Discovery Using Scientific Knowledge and Data
Da: Revaluation Books, Exeter, Regno Unito
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EUR 67,78
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Aggiungi al carrelloPaperback. Condizione: Brand New. 442 pages. 10.00x7.00x10.00 inches. In Stock.
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Knowledge Guided Machine Learning : Accelerating Discovery Using Scientific Knowledge and Data
Da: GreatBookPrices, Columbia, MD, U.S.A.
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EUR 63,33
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Knowledge Guided Machine Learning : Accelerating Discovery Using Scientific Knowledge and Data
Da: GreatBookPricesUK, Woodford Green, Regno Unito
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EUR 63,34
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Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
Da: Kennys Bookstore, Olney, MD, U.S.A.
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EUR 80,55
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Aggiungi al carrelloCondizione: New. 2024. 1st Edition. paperback. . . . . . Books ship from the US and Ireland.
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Knowledge Guided Machine Learning : Accelerating Discovery Using Scientific Knowledge and Data
Da: GreatBookPricesUK, Woodford Green, Regno Unito
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EUR 70,16
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Knowledge Guided Machine Learning (Paperback)
Editore: Taylor & Francis Ltd, London, 2024
ISBN 10: 036769820X ISBN 13: 9780367698201
Lingua: Inglese
Da: AussieBookSeller, Truganina, VIC, Australia
Valutazione del venditore 5 su 5 stelle
EUR 63,84
Convertire valutaEUR 31,53 per la spedizione da Australia a ItaliaQuantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: new. Paperback. Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines. Yet, these "black-box" ML models have found limited success due to their inability to work well in the presence of limited training data and generalize to unseen scenarios. As a result, there is a growing interest in the scientific community on creating a new generation of methods that integrate scientific knowledge in ML frameworks. This emerging field, called scientific knowledge-guided ML (KGML), seeks a distinct departure from existing "data-only" or "scientific knowledge-only" methods to use knowledge and data at an equal footing. Indeed, KGML involves diverse scientific and ML communities, where researchers and practitioners from various backgrounds and application domains are continually adding richness to the problem formulations and research methods in this emerging field. Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data provides an introduction to this rapidly growing field by discussing some of the common themes of research in KGML using illustrative examples, case studies, and reviews from diverse application domains and research communities as book chapters by leading researchers. KEY FEATURES First-of-its-kind book in an emerging area of research that is gaining widespread attention in the scientific and data science fields Accessible to a broad audience in data science and scientific and engineering fields Provides a coherent organizational structure to the problem formulations and research methods in the emerging field of KGML using illustrative examples from diverse application domains Contains chapters by leading researchers, which illustrate the cutting-edge research trends, opportunities, and challenges in KGML research from multiple perspectives Enables cross-pollination of KGML problem formulations and research methods across disciplines Highlights critical gaps that require further investigation by the broader community of researchers and practitioners to realize the full potential of KGML Knowledge Guided Machine Learning provides an introduction to this rapidly growing field by discussing some of the common themes of research in SGML, using illustrative examples and case studies from diverse application domains and research communities as contributed book chapters. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Knowledge Guided Machine Learning (Paperback)
Editore: Taylor & Francis Ltd, London, 2024
ISBN 10: 036769820X ISBN 13: 9780367698201
Lingua: Inglese
Da: CitiRetail, Stevenage, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 69,01
Convertire valutaEUR 34,37 per la spedizione da Regno Unito a ItaliaQuantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: new. Paperback. Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines. Yet, these "black-box" ML models have found limited success due to their inability to work well in the presence of limited training data and generalize to unseen scenarios. As a result, there is a growing interest in the scientific community on creating a new generation of methods that integrate scientific knowledge in ML frameworks. This emerging field, called scientific knowledge-guided ML (KGML), seeks a distinct departure from existing "data-only" or "scientific knowledge-only" methods to use knowledge and data at an equal footing. Indeed, KGML involves diverse scientific and ML communities, where researchers and practitioners from various backgrounds and application domains are continually adding richness to the problem formulations and research methods in this emerging field. Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data provides an introduction to this rapidly growing field by discussing some of the common themes of research in KGML using illustrative examples, case studies, and reviews from diverse application domains and research communities as book chapters by leading researchers. KEY FEATURES First-of-its-kind book in an emerging area of research that is gaining widespread attention in the scientific and data science fields Accessible to a broad audience in data science and scientific and engineering fields Provides a coherent organizational structure to the problem formulations and research methods in the emerging field of KGML using illustrative examples from diverse application domains Contains chapters by leading researchers, which illustrate the cutting-edge research trends, opportunities, and challenges in KGML research from multiple perspectives Enables cross-pollination of KGML problem formulations and research methods across disciplines Highlights critical gaps that require further investigation by the broader community of researchers and practitioners to realize the full potential of KGML Knowledge Guided Machine Learning provides an introduction to this rapidly growing field by discussing some of the common themes of research in SGML, using illustrative examples and case studies from diverse application domains and research communities as contributed book chapters. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Knowledge Guided Machine Learning (Paperback)
Editore: Taylor & Francis Ltd, London, 2024
ISBN 10: 036769820X ISBN 13: 9780367698201
Lingua: Inglese
Da: Grand Eagle Retail, Mason, OH, U.S.A.
Valutazione del venditore 5 su 5 stelle
EUR 67,39
Convertire valutaEUR 63,91 per la spedizione da U.S.A. a ItaliaQuantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: new. Paperback. Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines. Yet, these "black-box" ML models have found limited success due to their inability to work well in the presence of limited training data and generalize to unseen scenarios. As a result, there is a growing interest in the scientific community on creating a new generation of methods that integrate scientific knowledge in ML frameworks. This emerging field, called scientific knowledge-guided ML (KGML), seeks a distinct departure from existing "data-only" or "scientific knowledge-only" methods to use knowledge and data at an equal footing. Indeed, KGML involves diverse scientific and ML communities, where researchers and practitioners from various backgrounds and application domains are continually adding richness to the problem formulations and research methods in this emerging field. Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data provides an introduction to this rapidly growing field by discussing some of the common themes of research in KGML using illustrative examples, case studies, and reviews from diverse application domains and research communities as book chapters by leading researchers. KEY FEATURES First-of-its-kind book in an emerging area of research that is gaining widespread attention in the scientific and data science fields Accessible to a broad audience in data science and scientific and engineering fields Provides a coherent organizational structure to the problem formulations and research methods in the emerging field of KGML using illustrative examples from diverse application domains Contains chapters by leading researchers, which illustrate the cutting-edge research trends, opportunities, and challenges in KGML research from multiple perspectives Enables cross-pollination of KGML problem formulations and research methods across disciplines Highlights critical gaps that require further investigation by the broader community of researchers and practitioners to realize the full potential of KGML Knowledge Guided Machine Learning provides an introduction to this rapidly growing field by discussing some of the common themes of research in SGML, using illustrative examples and case studies from diverse application domains and research communities as contributed book chapters. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Knowledge Guided Machine Learning : Accelerating Discovery Using Scientific Knowledge and Data
Da: GreatBookPrices, Columbia, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
EUR 119,00
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EUR 113,44
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Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
Da: Majestic Books, Hounslow, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 130,20
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Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 136,96
Convertire valutaEUR 7,06 per la spedizione da Regno Unito a ItaliaQuantità: 1 disponibili
Aggiungi al carrelloHardback. Condizione: New. New copy - Usually dispatched within 4 working days. 209.
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Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
Da: Ria Christie Collections, Uxbridge, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 137,62
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Knowledge Guided Machine Learning : Accelerating Discovery Using Scientific Knowledge and Data
Da: GreatBookPrices, Columbia, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
EUR 133,36
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Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
Da: Books Puddle, New York, NY, U.S.A.
Valutazione del venditore 4 su 5 stelle
EUR 146,33
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Aggiungi al carrelloCondizione: New. 1st edition NO-PA16APR2015-KAP.
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Knowledge Guided Machine Learning : Accelerating Discovery Using Scientific Knowledge and Data
Da: GreatBookPricesUK, Woodford Green, Regno Unito
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EUR 136,95
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Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
Da: Biblios, Frankfurt am main, HESSE, Germania
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EUR 153,61
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Knowledge Guided Machine Learning : Accelerating Discovery Using Scientific Knowledge and Data
Da: GreatBookPricesUK, Woodford Green, Regno Unito
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EUR 150,09
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Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
Valutazione del venditore 5 su 5 stelle
EUR 121,03
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Knowledge Guided Machine Learning: Accelerating Discovery Using Scientific Knowledge and Data
Da: Revaluation Books, Exeter, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 184,06
Convertire valutaEUR 11,46 per la spedizione da Regno Unito a ItaliaQuantità: 2 disponibili
Aggiungi al carrelloHardcover. Condizione: Brand New. 448 pages. 10.00x7.00x0.94 inches. In Stock.
