Machine Learning with Neural Networks, Bernhard Mehlig

Автор: Alessandra Lintas; Stefano Rovetta; Paul F.M.J. Ve
Название: Artificial Neural Networks and Machine Learning -- ICANN 2017
ISBN: 3319685996 ISBN-13(EAN): 9783319685991
Издательство: Springer
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Цена: 65210.00 T
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Описание: The two volume set, LNCS 10613 and 10614, constitutes the proceedings of then 26th International Conference on Artificial Neural Networks, ICANN 2017, held in Alghero, Italy, in September 2017. The 128 full papers included in this volume were carefully reviewed and selected from 270 submissions.

Автор: Alessandra Lintas; Stefano Rovetta; Paul F.M.J. Ve
Название: Artificial Neural Networks and Machine Learning – ICANN 2017
ISBN: 3319686119 ISBN-13(EAN): 9783319686110
Издательство: Springer
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Цена: 102480.00 T
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Описание: The two volume set, LNCS 10613 and 10614, constitutes the proceedings of then 26th International Conference on Artificial Neural Networks, ICANN 2017, held in Alghero, Italy, in September 2017. The 128 full papers included in this volume were carefully reviewed and selected from 270 submissions.

Автор: Goldberg Yoav
Название: Neural Network Methods in Natural Language Processing
ISBN: 1627052984 ISBN-13(EAN): 9781627052986
Издательство: Mare Nostrum (Eurospan)
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Цена: 76690.00 T
Наличие на складе: Нет в наличии.
Описание: Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries.The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.

Автор: Oswald Campesato
Название: Natural Language Processing Fundamentals for Developersbility of Aircraft Gas Turbine Combustors
ISBN: 1683926579 ISBN-13(EAN): 9781683926573
Издательство: Mare Nostrum (Eurospan)
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Цена: 55440.00 T
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Описание: A book for developers who are looking for an overview of basic concepts in Natural Language Processing. It casts a wide net of techniques to help developers who have a range of technical backgrounds. Numerous code samples and listings are included to support myriad topics.

Автор: Raschka, Sebastian Mirjalili, Vahid
Название: Python machine learning -
ISBN: 1787125939 ISBN-13(EAN): 9781787125933
Издательство: Неизвестно
Цена: 53940.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This second edition of Python Machine Learning by Sebastian Raschka is for developers and data scientists looking for a practical approach to machine learning and deep learning. In this updated edition, you`ll explore the machine learning process using Python and the latest open source technologies, including scikit-learn and TensorFlow 1.x.

Автор: Aliev Rafik Aziz
Название: Arithmetic of Z-Numbers
ISBN: 9814675288 ISBN-13(EAN): 9789814675284
Издательство: World Scientific Publishing
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Цена: 110880.00 T
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Описание: Real-world information is imperfect and is usually described in natural language (NL). Moreover, this information is often partially reliable and a degree of reliability is also expressed in NL.

Автор: Venkatesan, Ragav,
Название: Convolutional Neural Networks In Vi
ISBN: 1498770398 ISBN-13(EAN): 9781498770392
Издательство: Taylor&Francis
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Цена: 168430.00 T
Наличие на складе: Невозможна поставка.
Описание: This book covers the fundamentals in designing and deploying techniques using deep architectures. It is intended to serve as a beginner`s guide to engineers or students who want to have a quick start on learning and/or building deep learning systems.

Автор: Villa
Название: Artificial Neural Networks and Machine Learning – ICANN 2016
ISBN: 3319447807 ISBN-13(EAN): 9783319447803
Издательство: Springer
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Цена: 68950.00 T
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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.

Автор: Villa
Название: Artificial Neural Networks and Machine Learning – ICANN 2016
ISBN: 3319447777 ISBN-13(EAN): 9783319447773
Издательство: Springer
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Цена: 68950.00 T
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.

Автор: Stefan Wermter; Cornelius Weber; Wlodzislaw Duch;
Название: Artificial Neural Networks and Machine Learning -- ICANN 2014
ISBN: 3319111787 ISBN-13(EAN): 9783319111780
Издательство: Springer
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Цена: 89440.00 T
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Описание: The book constitutes the proceedings of the 24th International Conference on Artificial Neural Networks, ICANN 2014, held in Hamburg, Germany, in September 2014. The 107 papers included in the proceedings were carefully reviewed and selected from 173 submissions. The focus of the papers is on following topics: recurrent networks;

Название: Evolutionary approach to machine learning and deep neural networks.
ISBN: 9811301999 ISBN-13(EAN): 9789811301995
Издательство: Springer
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Цена: 139750.00 T
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Описание: This book provides theoretical and practical knowledge about a methodology for evolutionary algorithm-based search strategy with the integration of several machine learning and deep learning techniques. These include convolutional neural networks, Gr?bner bases, relevance vector machines, transfer learning, bagging and boosting methods, clustering techniques (affinity propagation), and belief networks, among others. The development of such tools contributes to better optimizing methodologies. Beginning with the essentials of evolutionary algorithms and covering interdisciplinary research topics, the contents of this book are valuable for different classes of readers: novice, intermediate, and also expert readers from related fields.Following the chapters on introduction and basic methods, Chapter 3 details a new research direction, i.e., neuro-evolution, an evolutionary method for the generation of deep neural networks, and also describes how evolutionary methods are extended in combination with machine learning techniques. Chapter 4 includes novel methods such as particle swarm optimization based on affinity propagation (PSOAP), and transfer learning for differential evolution (TRADE), another machine learning approach for extending differential evolution.The last chapter is dedicated to the state of the art in gene regulatory network (GRN) research as one of the most interesting and active research fields. The author describes an evolving reaction network, which expands the neuro-evolution methodology to produce a type of genetic network suitable for biochemical systems and has succeeded in designing genetic circuits in synthetic biology. The author also presents real-world GRN application to several artificial intelligent tasks, proposing a framework of motion generation by GRNs (MONGERN), which evolves GRNs to operate a real humanoid robot.

Автор: Zhang
Название: Toward Deep Neural Networks
ISBN: 1138387037 ISBN-13(EAN): 9781138387034
Издательство: Taylor&Francis
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Цена: 127600.00 T
Наличие на складе: Нет в наличии.
Описание: This book introduces deep neural networks, with a focus on the weights-and-structure determination (WASD) algorithm. Based on the authors` 20 years of research experience on neuronets, the book explores the models, algorithms, and applications of the WASD neuronet.