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Deep Learning Neural Networks: Design And Case Studies, Graupe Daniel


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Цена: 11563.00р.
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Автор: Graupe Daniel
Название:  Deep Learning Neural Networks: Design And Case Studies
ISBN: 9789813146440
Издательство: World Scientific Publishing
Классификация:
ISBN-10: 9813146443
Обложка/Формат: Hardback
Страницы: 280
Вес: 0.63 кг.
Дата издания: 02.08.2016
Серия: Computing & IT
Язык: English
Размер: 249 x 160 x 20
Читательская аудитория: College/higher education
Ключевые слова: Neural networks & fuzzy systems, COMPUTERS / Intelligence (AI) & Semantics,COMPUTERS / Neural Networks,COMPUTERS / Software Development & Engineering / Systems Analysis & Design
Основная тема: Computer Science
Ссылка на Издательство: Link
Поставляется из: Англии
Описание:

Deep Learning Neural Networks is the fastest growing field in machine learning. It serves as a powerful computational tool for solving prediction, decision, diagnosis, detection and decision problems based on a well-defined computational architecture. It has been successfully applied to a broad field of applications ranging from computer security, speech recognition, image and video recognition to industrial fault detection, medical diagnostics and finance.

This comprehensive textbook is the first in the new emerging field. Numerous case studies are succinctly demonstrated in the text. It is intended for use as a one-semester graduate-level university text and as a textbook for research and development establishments in industry, medicine and financial research.


Дополнительное описание: Contents: Acknowledgements; Preface; Deep Learning Neural Networks: Methodology and Scope; Basic Concepts of Neural Networks; Back Propagation; The Cognitron and Neocognitron; Deep Learning Convolutional Neural Networks; LAMSTAR-1 and LAMSTAR-2 Neural Net



Deep Learning Neural Networks: Design And Case Studies

Автор: Graupe Daniel
Название: Deep Learning Neural Networks: Design And Case Studies
ISBN: 9813146451 ISBN-13(EAN): 9789813146457
Издательство: World Scientific Publishing
Рейтинг:
Цена: 6336.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

Deep Learning Neural Networks is the fastest growing field in machine learning. It serves as a powerful computational tool for solving prediction, decision, diagnosis, detection and decision problems based on a well-defined computational architecture. It has been successfully applied to a broad field of applications ranging from computer security, speech recognition, image and video recognition to industrial fault detection, medical diagnostics and finance.

This comprehensive textbook is the first in the new emerging field. Numerous case studies are succinctly demonstrated in the text. It is intended for use as a one-semester graduate-level university text and as a textbook for research and development establishments in industry, medicine and financial research.

Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies

Автор: Kelleher John D., Macnamee Brian, D`Arcy Aoife
Название: Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies
ISBN: 0262029448 ISBN-13(EAN): 9780262029445
Издательство: MIT Press
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Цена: 13543.00 р.
Наличие на складе: Нет в наличии.

Описание:

A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context.

After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals.

On-Line Learning in Neural Networks

Автор: Saad
Название: On-Line Learning in Neural Networks
ISBN: 0521652634 ISBN-13(EAN): 9780521652636
Издательство: Cambridge Academ
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Цена: 18691.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: On-line learning is one of the most commonly used techniques for training large layered networks. Traditional methods have been recently complemented by ones from statistical physics and Bayesian statistics to provide more insight and deeper understanding of existing algorithms. This book presents a coherent picture of the state-of-the-art.

Project Management: Case Studies, 4th Edition

Автор: Kerzner
Название: Project Management: Case Studies, 4th Edition
ISBN: 1118022289 ISBN-13(EAN): 9781118022283
Издательство: Wiley
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Цена: 8316.00 р.
Наличие на складе: Поставка под заказ.

Описание: Case studies have traditionally made up a significant portion of  project management education and training. The Kerzner case studies book was planned to package a broad range of case studies in one book to be used in college or professional training courses (as an ancillary to either Kerzner's book or other project management texts).  The book has grown to become a very successful product on its own.  For this fourth edition Kerzner will add a number of new cases covering value measurement in project management - we will retain the well recevied "super case" which covers all aspects of project management and may be used as a capstone for a course. 

A Theory of Learning and Generalization: With Applications to Neural Networks and Control Systems

Название: A Theory of Learning and Generalization: With Applications to Neural Networks and Control Systems
ISBN: 1849968675 ISBN-13(EAN): 9781849968676
Издательство: Springer
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Цена: 23508.00 р.
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Описание: How does a machine learn a new concept on the basis of examples? This second edition takes account of important new developments in the field. It also deals extensively with the theory of learning control systems, now comparably mature to learning of neural networks.

Artificial Neural Networks and Machine Learning – ICANN 2016

Автор: Villa
Название: Artificial Neural Networks and Machine Learning – ICANN 2016
ISBN: 3319447777 ISBN-13(EAN): 9783319447773
Издательство: Springer
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Цена: 10342.00 р.
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Описание: The two volume set, LNCS 9886 + 9887, constitutes the proceedings of the 25th International Conference on Artificial Neural Networks, ICANN 2016, held in Barcelona, Spain, in September 2016. The 121 full papers included in this volume were carefully reviewed and selected from 227 submissions.

Artificial Neural Networks and Machine Learning – ICANN 2016

Автор: Villa
Название: Artificial Neural Networks and Machine Learning – ICANN 2016
ISBN: 3319447807 ISBN-13(EAN): 9783319447803
Издательство: Springer
Рейтинг:
Цена: 10342.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The two volume set, LNCS 9886 + 9887, constitutes the proceedings of the 25th International Conference on Artificial Neural Networks, ICANN 2016, held in Barcelona, Spain, in September 2016. The 121 full papers included in this volume were carefully reviewed and selected from 227 submissions.


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