9783031010378 - neural network methods for natural language processing di goldberg, yoav (19 risultati)

Lingua: Inglese
Editore: Springer 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Lingua: Inglese
Editore: Springer 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Lingua: Inglese
Editore: Springer 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Lingua: Inglese
Editore: Springer 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Lingua: Inglese
Editore: Springer International Publishing AG, CH 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Paperback. Condizione: New. 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.

Lingua: Inglese
Editore: Springer 2017-04 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Lingua: Inglese
Editore: Springer 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Lingua: Inglese
Editore: Springer 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Editore: Springer 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Condizione: New. 1st edition NO-PA16APR2015-KAP.

Lingua: Inglese
Editore: Springer 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Lingua: Inglese
Editore: Springer International Publishing, Springer International Publishing 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
Altre immaginiLingua: Inglese
Editore: Springer International Publishing 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Taschenbuch. Condizione: Neu. Neural Network Methods for Natural Language Processing | Yoav Goldberg | Taschenbuch | ccxcii | Englisch | 2017 | Springer International Publishing | EAN 9783031010378 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot…]com | Anbieter: preigu.

Lingua: Inglese
Editore: Springer International Publishing AG, CH 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Paperback. Condizione: New. 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.

Lingua: Inglese
Editore: Springer 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Condizione: new. Questo è un articolo print on demand.

Lingua: Inglese
Editore: Springer International Publishing Apr 2017 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 m…achine 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. 312 pp. Englisch.

Lingua: Inglese
Editore: Springer 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Lingua: Inglese
Editore: Springer 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Lingua: Inglese
Editore: Springer, Berlin|Springer International Publishing|Morgan & Claypool|Springer 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 fee.

Lingua: Inglese
Editore: Springer International Publishing, Springer International Publishing Apr 2017 2017
Serie: Synthesis Lectures on Human Language Technologies, Libro 4 di 11. Libro 4 di 11 - Synthesis Lectures on Human Language Technologies
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 machi…ne 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.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 312 pp. Englisch.