Machine Learning Paradigms, Aristomenis S. Lampropoulos; George A. Tsihrintzis

Автор: Peter Norvig
Название: Paradigms of Artificial Intelligence Programming,
ISBN: 1558601910 ISBN-13(EAN): 9781558601918
Издательство: Elsevier Science
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Цена: 9599.00 р.
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Описание: Paradigms of AI Programming teaches advanced Common Lisp techniques in the context of building major AI systems.

Автор: Christopher M. Bishop
Название: Pattern Recognition and Machine Learning
ISBN: 0387310738 ISBN-13(EAN): 9780387310732
Издательство: Springer
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Цена: 11878.00 р.
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Описание: Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Автор: Mirjana Ivanovi?; Lakhmi C. Jain
Название: E-Learning Paradigms and Applications
ISBN: 364241964X ISBN-13(EAN): 9783642419645
Издательство: Springer
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Цена: 19591.00 р.
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Описание: This book presents the state-of-the-art of e-learning and tutoring systems, and discusses their capabilities and benefits that stem from integrating software agents. It includes various case studies to validate the usefulness of the presented paradigms.

Автор: Mirjana Ivanovi?; Lakhmi C. Jain
Название: E-Learning Paradigms and Applications
ISBN: 3662509466 ISBN-13(EAN): 9783662509463
Издательство: Springer
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Цена: 15672.00 р.
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Описание: This book presents the state-of-the-art of e-learning and tutoring systems, and discusses their capabilities and benefits that stem from integrating software agents. It includes various case studies to validate the usefulness of the presented paradigms.

Автор: Lakhmi C. Jain; Janusz Kacprzyk
Название: New Learning Paradigms in Soft Computing
ISBN: 3790814369 ISBN-13(EAN): 9783790814361
Издательство: Springer
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Цена: 23058.00 р.
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Описание: The purpose of this volume is to present some new learning paradigms that have been triggered, or at least strongly influenced by soft computing tools and techniques, mainly related to neural networks, fuzzy logic, rough sets and evolutionary computations.

Автор: Lakhmi C. Jain; Janusz Kacprzyk
Название: New Learning Paradigms in Soft Computing
ISBN: 3790824992 ISBN-13(EAN): 9783790824995
Издательство: Springer
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Цена: 23058.00 р.
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Описание: The purpose of this volume is to present some new learning paradigms that have been triggered, or at least strongly influenced by soft computing tools and techniques, mainly related to neural networks, fuzzy logic, rough sets, and evolutionary computations.

Автор: Nikhil Ichalkaranje; Ajita Ichalkaranje
Название: Intelligent Paradigms for Assistive and Preventive Healthcare
ISBN: 3642068626 ISBN-13(EAN): 9783642068621
Издательство: Springer
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Цена: 19589.00 р.
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Описание: Intelligent paradigms play a tremendous role in the field of Assistive and Preventive Healthcare (APH). This book presents some of the latest research in the field of APH by most prestigious researchers. Coverage includes Multimedia medical informatics; Electronic Locomotion Aids, and Multimedia Communication Systems for the Blind;

Автор: Margarita Sordo; Sachin Vaidya
Название: Advanced Computational Intelligence Paradigms in Healthcare - 3
ISBN: 3642096441 ISBN-13(EAN): 9783642096440
Издательство: Springer
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Цена: 23757.00 р.
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Описание: This volume details the latest state-of-the-art research on computational intelligence paradigms in healthcare in the intelligent agent environment. The book presents seven chapters selected from the rapidly growing application areas of computational intelligence to healthcare systems.

Автор: Dionisios N. Sotiropoulos; George A. Tsihrintzis
Название: Machine Learning Paradigms
ISBN: 3319471929 ISBN-13(EAN): 9783319471921
Издательство: Springer
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Цена: 20962.00 р.
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Описание: The topic of this monograph falls within the, so-called, biologically motivated computing paradigm, in which biology provides the source of models and inspiration towards the development of computational intelligence and machine learning systems. Specifically, artificial immune systems are presented as a valid metaphor towards the creation of abstract and high level representations of biological components or functions that lay the foundations for an alternative machine learning paradigm. Therefore, focus is given on addressing the primary problems of Pattern Recognition by developing Artificial Immune System-based machine learning algorithms for the problems of Clustering, Classification and One-Class Classification. Pattern Classification, in particular, is studied within the context of the Class Imbalance Problem. The main source of inspiration stems from the fact that the Adaptive Immune System constitutes one of the most sophisticated biological systems that is exceptionally evolved in order to continuously address an extremely unbalanced pattern classification problem, namely, the self / non-self discrimination process. The experimental results presented in this monograph involve a wide range of degenerate binary classification problems where the minority class of interest is to be recognized against the vast volume of the majority class of negative patterns. In this context, Artificial Immune Systems are utilized for the development of personalized software as the core mechanism behind the implementation of Recommender Systems.The book will be useful to researchers, practitioners and graduate students dealing with Pattern Recognition and Machine Learning and their applications in Personalized Software and Recommender Systems. It is intended for both the expert/researcher in these fields, as well as for the general reader in the field of Computational Intelligence and, more generally, Computer Science who wishes to learn more about the field of Intelligent Computing Systems and its applications. An extensive list of bibliographic references at the end of each chapter guides the reader to probe further into application area of interest to him/her.

Автор: Aristomenis S. Lampropoulos; George A. Tsihrintzis
Название: Machine Learning Paradigms
ISBN: 3319191349 ISBN-13(EAN): 9783319191348
Издательство: Springer
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Цена: 15672.00 р.
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Описание: This timely book presents Applications in Recommender Systems which are making recommendations using machine learning algorithms trained via examples of content the user likes or dislikes.