Editore: Morgan & Claypool Publishers, 2013
ISBN 10: 162705197X ISBN 13: 9781627051972
Lingua: Inglese
Da: suffolkbooks, Center moriches, NY, U.S.A.
paperback. Condizione: Very Good. Fast Shipping - Safe and Secure 7 days a week!
hardcover. Condizione: Good.
Hardcover. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Da: Textbooks_Source, Columbia, MO, U.S.A.
Prima edizione
hardcover. 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).
hardcover. 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.
Editore: Morgan & Claypool Publishers, 2013
ISBN 10: 162705197X ISBN 13: 9781627051972
Lingua: Inglese
Da: GoldBooks, Denver, CO, U.S.A.
Condizione: new.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New.
Da: Majestic Books, Hounslow, Regno Unito
EUR 67,82
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New. x, 315 pages, illustrations some color.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition.
Condizione: New. 1st edition NO-PA16APR2015-KAP.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 63,30
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In English.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 63,59
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
hardcover. Condizione: Fine. in great condition.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 67,19
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. x, 315 pages, illustrations some color First edition Includes bibliographical references and index.
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 67,20
Quantità: 1 disponibili
Aggiungi al carrelloPaperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days. 453.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 73,12
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 76,60
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New. x, 315 pages, illustrations some color.
Da: Revaluation Books, Exeter, Regno Unito
EUR 97,50
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 330 pages. 10.00x7.00x10.00 inches. In Stock.
Da: ReviBlio, Barcelona, B, Spagna
Prima edizione
EUR 65,00
Quantità: 1 disponibili
Aggiungi al carrelloCondition: Very good. This book a is a comprehensive, landmark textbook that provides a general framework for constructing and using probabilistic models of complex systems. Its primary focus is on how to represent and reason about uncertainty in complex, real-world domains like computer vision, robotics, and computational biology. The book is structured around the three fundamental cornerstones of the probabilistic graphical model (PGM) framework: Representation: Discusses various models, including Bayesian Networks (directed graphs) and Undirected Markov Networks, as ways to compactly encode joint probability distributions over many variables using conditional independence assumptions. Inference: Details the algorithms and techniques (both exact and approximate, like belief propagation and sampling methods) for answering probabilistic queries, such as finding the probability of an event given some evidence. Learning: Covers methods for automatically constructing the models from data, including estimating model parameters and learning the underlying graph structure. Finally, the book extends the framework to cover advanced topics such as causal reasoning and decision making under uncertainty. It is widely regarded as a definitive reference for students and researchers in artificial intelligence and machine learning.
Hardcover. Condizione: new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks.
Editore: Taylor & Francis Ltd, London, 2024
ISBN 10: 1032039507 ISBN 13: 9781032039503
Lingua: Inglese
Da: CitiRetail, Stevenage, Regno Unito
EUR 78,34
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: new. Paperback. This book presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining knowledge from Big Data and in interpreting decisions. It explores Bayesian network learning, Control Chart, Reinforcement Learning for multicriteria DSS, Anomaly Detection in Smart Manufacturing with Federated Learning, DSS in healthcare, DSS for supply chain management, etc. Researchers and practitioners alike will benefit from this book to enhance the understanding of machine learning, Probabilistic Graphical Models, and their uses in DSS in the context of decision making with uncertainty. The real-world case studies in various fields with guidance and recommendations for the practical applications of these studies are introduced in each chapter. This book presents recent advancements in research, new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models. The book undertakes to stimulate scientific exchange, ideas, and experiences in the field of DSS applications. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 124,08
Quantità: 2 disponibili
Aggiungi al carrelloCondizione: New. In.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 130,31
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New. pp. 1280.
Da: Majestic Books, Hounslow, Regno Unito
EUR 138,16
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: New. pp. 1280.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New.
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 197,43
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. 1st edition NO-PA16APR2015-KAP.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 133,32
Quantità: 1 disponibili
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.
Da: Majestic Books, Hounslow, Regno Unito
EUR 210,48
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New.