Da: BooksRun, Philadelphia, PA, U.S.A.
EUR 41,65
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Aggiungi al carrelloHardcover. Condizione: Good. 1. It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience.
Da: Textbooks_Source, Columbia, MO, U.S.A.
Prima edizione
EUR 41,92
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Aggiungi al carrellohardcover. Condizione: Good. 1st Edition. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
Da: Bellwetherbooks, McKeesport, PA, U.S.A.
EUR 82,20
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Aggiungi al carrellohardcover. Condizione: Very Good. Very Good Condition - May show some limited signs of wear and may have a remainder mark. Pages and dust cover are intact and not marred by notes or highlighting.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 90,06
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Aggiungi al carrelloCondizione: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 121,89
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Aggiungi al carrelloCondizione: New.
Da: Majestic Books, Hounslow, Regno Unito
EUR 116,50
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Aggiungi al carrelloCondizione: New. pp. 1280.
Da: ALLBOOKS1, Direk, SA, Australia
EUR 125,84
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 109,03
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Aggiungi al carrelloCondizione: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 108,76
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Aggiungi al carrelloCondizione: New.
Da: ALLBOOKS1, Direk, SA, Australia
EUR 129,34
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Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 129,47
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Editore: Mit Press, 2009
Lingua: Inglese
Da: Books in my Basket, New Delhi, India
EUR 123,65
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Aggiungi al carrelloHardcover. Condizione: New. ISBN:9780262013192.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 125,90
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Aggiungi al carrelloCondizione: New. In.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 128,72
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Aggiungi al carrelloCondizione: New. pp. 1280.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 129,17
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: Buchpark, Maidenhead, Berkshire, Regno Unito
EUR 74,72
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Aggiungi al carrelloCondizione: Very Good. Condition: Very Good, Pages: 1270, Size: 23.6x20.9x5.
Da: UK BOOKS STORE, London, LONDO, Regno Unito
EUR 191,39
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Aggiungi al carrelloHardcover. Condizione: Brand New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 7-11 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India,& United states & United Kingdom. Depending on your location and availability.
Da: Toscana Books, AUSTIN, TX, U.S.A.
EUR 196,27
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Aggiungi al carrelloHardcover. Condizione: new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 133,32
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Aggiungi al carrelloHardcover. Condizione: Sehr gut. Gebraucht - Sehr gut Sg - leichte Beschädigungen oder Verschmutzungen, ungelesenes Mängelexemplar, gestempelt - A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions.Most tasks require a person or an automated system to reason to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality. Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.
EUR 141,68
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Aggiungi al carrelloBuch. Condizione: Neu. Neuware - A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions.Most tasks require a person or an automated system to reason to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality. Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.