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Representation Learning for Natural Language Processing
Anbieter: Books From California, Simi Valley, CA, USA
Verkäuferbewertung 4 von 5 Sternen
hardcover. Zustand: Very Good.
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Representation Learning for Natural Language Processing
Anbieter: Books From California, Simi Valley, CA, USA
Verkäuferbewertung 4 von 5 Sternen
hardcover. Zustand: Good. Book is bent.
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Representation Learning for Natural Language Processing
Sprache: Englisch
Verlag: Springer (edition 1st ed. 2020), 2020
ISBN 10: 9811555729 ISBN 13: 9789811555725
Hardcover. Zustand: Very Good. 1st ed. 2020. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
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Representation Learning for Natural Language Processing
Anbieter: GreatBookPrices, Columbia, MD, USA
Verkäuferbewertung 5 von 5 Sternen
Zustand: New.
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Representation Learning for Natural Language Processing
Anbieter: GreatBookPrices, Columbia, MD, USA
Verkäuferbewertung 5 von 5 Sternen
Zustand: As New. Unread book in perfect condition.
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Representation Learning for Natural Language Processing
Anbieter: California Books, Miami, FL, USA
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Zustand: New.
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Representation Learning for Natural Language Processing
Anbieter: GreatBookPrices, Columbia, MD, USA
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Representation Learning for Natural Language Processing
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
EUR 47,97
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Representation Learning for Natural Language Processing
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
EUR 47,97
EUR 13,85 Versand
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In den WarenkorbZustand: New. In.
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Representation Learning for Natural Language Processing
Verlag: Springer
Anbieter: Academic Book Solutions, Medford, NY, USA
Verkäuferbewertung 5 von 5 Sternen
hardcover. Zustand: VeryGood. A copy that may have been read, very minimal wear and tear. May have a remainder mark.
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Representation Learning for Natural Language Processing
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
EUR 47,96
EUR 17,35 Versand
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Representation Learning for Natural Language Processing
Anbieter: GreatBookPrices, Columbia, MD, USA
Verkäuferbewertung 5 von 5 Sternen
Zustand: As New. Unread book in perfect condition.
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Zustand: New. pp. XXIV, 334 131 illus., 99 illus. in color. 1st ed. 2020 edition NO-PA16APR2015-KAP.
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Representation Learning for Natural Language Processing
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
EUR 52,75
EUR 17,35 Versand
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In den WarenkorbZustand: As New. Unread book in perfect condition.
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Zustand: New. 2nd ed. 2023 edition NO-PA16APR2015-KAP.
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Representation Learning for Natural Language Processing
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
EUR 60,06
EUR 13,85 Versand
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Representation Learning for Natural Language Processing
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
EUR 60,05
EUR 17,35 Versand
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Representation Learning for Natural Language Processing
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
EUR 66,56
EUR 17,35 Versand
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In den WarenkorbZustand: As New. Unread book in perfect condition.
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Zustand: New. 2nd ed. 2023 edition NO-PA16APR2015-KAP.
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Representation Learning for Natural Language Processing
Sprache: Englisch
Verlag: Springer-Nature New York Inc, 2023
ISBN 10: 981991602X ISBN 13: 9789819916023
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
EUR 74,61
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In den WarenkorbPaperback. Zustand: Brand New. 2nd edition. 541 pages. 9.25x6.10x1.10 inches. In Stock.
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Internationale AusgabeREPRESENTATION LEARNING FOR NATURAL LANGUAGE PROCESSING 2ED (HB 2023)
Anbieter: UK BOOKS STORE, London, LONDO, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
EUR 96,21
EUR 6,93 Versand
Versand von Vereinigtes Königreich nach USAAnzahl: 1 verfügbar
In den WarenkorbZustand: New. Brand New ! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Representation Learning for Natural Language Processing
Sprache: Englisch
Verlag: Springer-Nature New York Inc, 2023
ISBN 10: 9819915996 ISBN 13: 9789819915996
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
EUR 89,87
EUR 14,45 Versand
Versand von Vereinigtes Königreich nach USAAnzahl: 2 verfügbar
In den WarenkorbHardcover. Zustand: Brand New. 2nd edition. 541 pages. 9.25x6.10x1.34 inches. In Stock.
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Taschenbuch. Zustand: Neu. Representation Learning for Natural Language Processing | Zhiyuan Liu (u. a.) | Taschenbuch | xxiv | Englisch | 2020 | Springer | EAN 9789811555756 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Taschenbuch. Zustand: Neu. Representation Learning for Natural Language Processing | Zhiyuan Liu (u. a.) | Taschenbuch | xx | Englisch | 2023 | Springer | EAN 9789819916023 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Representation Learning for Natural Language Processing
Anbieter: Mispah books, Redhill, SURRE, Vereinigtes Königreich
Verkäuferbewertung 4 von 5 Sternen
EUR 86,95
EUR 28,91 Versand
Versand von Vereinigtes Königreich nach USAAnzahl: 1 verfügbar
In den WarenkorbPaperback. Zustand: New. New. book.
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Representation Learning for Natural Language Processing
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions.The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate andgraduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.
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Application of deep learning in natural language processing from word representation to ChatGPT(Chinese Edition)
Sprache: Englisch
Verlag: Posts and Telecommunications Press, 2023
ISBN 10: 7115613338 ISBN 13: 9787115613332
paperback. Zustand: New. Paperback. Pub Date: 2023-05 Pages: 203 Publisher: Posts and Telecommunications Press This book introduces the technical principles of deep learning and its application in natural language processing (NLP). which is currently popular and has broad application prospects. It briefly analyzes the relevant models and key technologies in various application directions in this field. including Transformer. BERT. GPT. etc. It brings together important ideas and research results from many papers and .
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Representation Learning for Natural Language Processing
Sprache: Englisch
Verlag: Springer, Springer Nature Singapore, 2023
ISBN 10: 981991602X ISBN 13: 9789819916023
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts. Part I presents the representation learning techniques for multiple language entries, including words, sentences and documents, as well as pre-training techniques. Part II then introduces the related representation techniques to NLP, including graphs, cross-modal entries, and robustness. Part III then introduces the representation techniques for the knowledge that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, legal domain knowledge and biomedical domain knowledge. Lastly, Part IV discusses the remaining challenges and future research directions.The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, socialnetwork analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.As compared to the first edition, the second edition (1) provides a more detailed introduction to representation learning in Chapter 1; (2) adds four new chapters to introduce pre-trained language models, robust representation learning, legal knowledge representation learning and biomedical knowledge representation learning; (3) updates recent advances in representation learning in all chapters; and (4) corrects some errors in the first edition. The new contents will be approximately 50%+ compared to the first edition. This is an open access book.
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Representation Learning for Natural Language Processing
Sprache: Englisch
Verlag: Springer, Springer Nature Singapore, 2023
ISBN 10: 9819915996 ISBN 13: 9789819915996
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts. Part I presents the representation learning techniques for multiple language entries, including words, sentences and documents, as well as pre-training techniques. Part II then introduces the related representation techniques to NLP, including graphs, cross-modal entries, and robustness. Part III then introduces the representation techniques for the knowledge that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, legal domain knowledge and biomedical domain knowledge. Lastly, Part IV discusses the remaining challenges and future research directions.The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, socialnetwork analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.As compared to the first edition, the second edition (1) provides a more detailed introduction to representation learning in Chapter 1; (2) adds four new chapters to introduce pre-trained language models, robust representation learning, legal knowledge representation learning and biomedical knowledge representation learning; (3) updates recent advances in representation learning in all chapters; and (4) corrects some errors in the first edition. The new contents will be approximately 50%+ compared to the first edition. This is an open access book.
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Representation Learning for Natural Language Processing
Sprache: Englisch
Verlag: Springer Nature Singapore, 2023
ISBN 10: 981991602X ISBN 13: 9789819916023
Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 544 | Sprache: Englisch | Produktart: Bücher | This book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts. Part I presents the representation learning techniques for multiple language entries, including words, sentences and documents, as well as pre-training techniques. Part II then introduces the related representation techniques to NLP, including graphs, cross-modal entries, and robustness. Part III then introduces the representation techniques for the knowledge that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, legal domain knowledge and biomedical domain knowledge. Lastly, Part IV discusses the remaining challenges and future research directions.The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, socialnetwork analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.As compared to the first edition, the second edition (1) provides a more detailed introduction to representation learning in Chapter 1; (2) adds four new chapters to introduce pre-trained language models, robust representation learning, legal knowledge representation learning and biomedical knowledge representation learning; (3) updates recent advances in representation learning in all chapters; and (4) corrects some errors in the first edition. The new contents will be approximately 50%+ compared to the first edition. This is an open access book.
