Prediction analysis knowledge representation (26 risultati)

Prediction and Analysis for Knowledge Representation and Machine Learning
Kumar, Avadhesh (EDT); Sagar, Shrddha (EDT); Kumar, T. Ganesh (EDT); Kumar, K Sampath (EDT)
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Prediction and Analysis for Knowledge Representation and Machine Learning
Kumar, Avadhesh (EDT); Sagar, Shrddha (EDT); Kumar, T. Ganesh (EDT); Kumar, K Sampath (EDT)
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
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PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Prediction and Analysis for Knowledge Representation and Machine Learning
Kumar, Avadhesh (EDT); Sagar, Shrddha (EDT); Kumar, T. Ganesh (EDT); Kumar, K Sampath (EDT)
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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EUR 76,50
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Condizione: As New. Unread book in perfect condition.

Prediction and Analysis for Knowledge Representation and Machine Learning
Kumar, Avadhesh (EDT); Sagar, Shrddha (EDT); Kumar, T. Ganesh (EDT); Kumar, K Sampath (EDT)
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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EUR 77,71
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Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
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Paperback. Condizione: New. A number of approaches are being defined for statistics and machine learning. These approaches are used for the identification of the process of the system and the models created from the system's perceived data, assisting scientists in the generation or refinement of current models. Machine learning is being studied extensively in science, particularly in bioinformatics, economics, social sciences, ecology, and climate science, but learning from data individually needs to be researched more for complex scenarios. Advanced knowledge representation approaches that can capture structural and process properties are necessary to provide meaningful knowledge to machine learning algorithms. It has a significant impact on comprehending difficult scientific problems.Prediction and Analysis for Knowledge Representation and Machine Learning demonstrates various knowledge representation and machine learning methodologies and architectures that will be active in the research field. The approaches are reviewed with real-life examples from a wide range of research topics. An understanding of a number of techniques and algorithms that are implemented in knowledge representation in machine learning is available through the book's website.Features: Examines the representational adequacy of needed knowledge representation Manipulates inferential adequacy for knowledge representation in order to produce new knowledge derived from the original information Improves inferential and acquisition efficiency by applying automatic methods to acquire new knowledge Covers the major challenges, concerns, and breakthroughs in knowledge representation and machine learning using the most up-to-date technology Describes the ideas of knowledge representation and related technologies, as well as their applications, in order to help humankind become better and smarterThis book serves as a reference book for researchers and practitioners who are working in the field of information technology and computer science in knowledge representation and machine learning for both basic and advanced concepts. Nowadays, it has become essential to develop adaptive, robust, scalable, and reliable applications and also design solutions for day-to-day problems. The edited book will be helpful for industry people and will also help beginners as well as high-level users for learning the latest things, which include both basic and advanced concepts.…

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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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EUR 111,84
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Paperback. Condizione: Brand New. 232 pages. 9.18x6.12x9.21 inches. In Stock.

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Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
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EUR 107,39
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Paperback. Condizione: New. A number of approaches are being defined for statistics and machine learning. These approaches are used for the identification of the process of the system and the models created from the system's perceived data, assisting scientists in the generation or refinement of current models. Machine learning is being studied extensively in science, particularly in bioinformatics, economics, social sciences, ecology, and climate science, but learning from data individually needs to be researched more for complex scenarios. Advanced knowledge representation approaches that can capture structural and process properties are necessary to provide meaningful knowledge to machine learning algorithms. It has a significant impact on comprehending difficult scientific problems.Prediction and Analysis for Knowledge Representation and Machine Learning demonstrates various knowledge representation and machine learning methodologies and architectures that will be active in the research field. The approaches are reviewed with real-life examples from a wide range of research topics. An understanding of a number of techniques and algorithms that are implemented in knowledge representation in machine learning is available through the book's website.Features: Examines the representational adequacy of needed knowledge representation Manipulates inferential adequacy for knowledge representation in order to produce new knowledge derived from the original information Improves inferential and acquisition efficiency by applying automatic methods to acquire new knowledge Covers the major challenges, concerns, and breakthroughs in knowledge representation and machine learning using the most up-to-date technology Describes the ideas of knowledge representation and related technologies, as well as their applications, in order to help humankind become better and smarterThis book serves as a reference book for researchers and practitioners who are working in the field of information technology and computer science in knowledge representation and machine learning for both basic and advanced concepts. Nowadays, it has become essential to develop adaptive, robust, scalable, and reliable applications and also design solutions for day-to-day problems. The edited book will be helpful for industry people and will also help beginners as well as high-level users for learning the latest things, which include both basic and advanced concepts.…

Prediction and Analysis for Knowledge Representation and Machine Learning
Kumar, Avadhesh (EDT); Sagar, Shrddha (EDT); Kumar, T. Ganesh (EDT); Kumar, K. Sampath (EDT)
- Rilegato
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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EUR 186,70
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Prediction and Analysis for Knowledge Representation and Machine Learning
Kumar, Avadhesh (EDT); Sagar, Shrddha (EDT); Kumar, T. Ganesh (EDT); Kumar, K. Sampath (EDT)
- Rilegato
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Condizione: New.

Prediction and Analysis for Knowledge Representation and Machine Learning
Kumar, Avadhesh (EDT); Sagar, Shrddha (EDT); Kumar, T. Ganesh (EDT); Kumar, K. Sampath (EDT)
- Rilegato
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Condizione: As New. Unread book in perfect condition.

Prediction and Analysis for Knowledge Representation and Machine Learning
Kumar, Avadhesh (EDT); Sagar, Shrddha (EDT); Kumar, T. Ganesh (EDT); Kumar, K. Sampath (EDT)
- Rilegato
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New. 1st edition NO-PA16APR2015-KAP.

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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Da: California Books, Miami, FL, U.S.A.California Books
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Hardcover. Condizione: Brand New. 248 pages. 9.25x6.19x0.56 inches. In Stock.

Prediction and Analysis for Knowledge Representation and Machine Learning
Kumar, Avadhesh (Galgotias Uni.)|Sagar, Shrddha (Galgotias Uni.)|Kumar, T. Ganesh|Sampath Kumar, K.
- Rilegato
- Print on Demand
Da: moluna, Greven, Germaniamoluna
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Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Avadhesh Kumar is PVC at Galgotias University, Greater Noida, Uttar Pradesh, India. He has more than 21 years of Academic and Research Experience. He was awarded Ph.D. in Computer Science & Engineering in 2010 from Thapar University..…

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- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A number of approaches are being defined for statistics and machine learning. These approaches are used for the identification of the process of the system and the models created from the system's perceived data, assisting scientists in the generation or refinement of current models. Machine learning is being studied extensively in science, particularly in bioinformatics, economics, social sciences, ecology, and climate science, but learning from data individually needs to be researched more for complex scenarios. Advanced knowledge representation approaches that can capture structural and process properties are necessary to provide meaningful knowledge to machine learning algorithms. It has a significant impact on comprehending difficult scientific problems.Prediction and Analysis for Knowledge Representation and Machine Learning demonstrates various knowledge representation and machine learning methodologies and architectures that will be active in the research field. The approaches are reviewed with real-life examples from a wide range of research topics. An understanding of a number of techniques and algorithms that are implemented in knowledge representation in machine learning is available through the book's website.Features:Examines the representational adequacy of needed knowledge representationManipulates inferential adequacy for knowledge representation in order to produce new knowledge derived from the original informationImproves inferential and acquisition efficiency by applying automatic methods to acquire new knowledgeCovers the major challenges, concerns, and breakthroughs in knowledge representation and machine learning using the most up-to-date technologyDescribes the ideas of knowledge representation and related technologies, as well as their applications, in order to help humankind become better and smarterThis book serves as a reference book for researchers and practitioners who are working in the field of information technology and computer science in knowledge representation and machine learning for both basic and advanced concepts. Nowadays, it has become essential to develop adaptive, robust, scalable, and reliable applications and also design solutions for day-to-day problems. The edited book will be helpful for industry people and will also help beginners as well as high-level users for learning the latest things, which include both basic and advanced concepts. 232 pp. Englisch.…

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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
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HRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

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Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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HRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A number of approaches are being defined for statistics and machine learning. These approaches are used for the identification of the process of the system and the models created from the system's perceived data, assisting scientists in the generation or refinement of current models. Machine learning is being studied extensively in science, particularly in bioinformatics, economics, social sciences, ecology, and climate science, but learning from data individually needs to be researched more for complex scenarios. Advanced knowledge representation approaches that can capture structural and process properties are necessary to provide meaningful knowledge to machine learning algorithms. It has a significant impact on comprehending difficult scientific problems.Prediction and Analysis for Knowledge Representation and Machine Learning demonstrates various knowledge representation and machine learning methodologies and architectures that will be active in the research field. The approaches are reviewed with real-life examples from a wide range of research topics. An understanding of a number of techniques and algorithms that are implemented in knowledge representation in machine learning is available through the book's website.Features:Examines the representational adequacy of needed knowledge representationManipulates inferential adequacy for knowledge representation in order to produce new knowledge derived from the original informationImproves inferential and acquisition efficiency by applying automatic methods to acquire new knowledgeCovers the major challenges, concerns, and breakthroughs in knowledge representation and machine learning using the most up-to-date technologyDescribes the ideas of knowledge representation and related technologies, as well as their applications, in order to help humankind become better and smarterThis book serves as a reference book for researchers and practitioners who are working in the field of information technology and computer science in knowledge representation and machine learning for both basic and advanced concepts. Nowadays, it has become essential to develop adaptive, robust, scalable, and reliable applications and also design solutions for day-to-day problems. The edited book will be helpful for industry people and will also help beginners as well as high-level users for learning the latest things, which include both basic and advanced concepts. …