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Aggiungi al carrelloCondizione: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.
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Aggiungi al carrelloHardcover. Condizione: As New. No Jacket. Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less 2.6.
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Aggiungi al carrelloPaperback. Condizione: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
EUR 50,24
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Aggiungi al carrelloCondizione: New. pp. 520.
EUR 48,95
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Aggiungi al carrelloCondizione: New. pp. 520.
Editore: Springer Nature Switzerland AG, 2023
ISBN 10: 3030966259 ISBN 13: 9783030966256
Lingua: Inglese
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 54,06
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Editore: Springer Nature Switzerland AG, 2023
ISBN 10: 3030966259 ISBN 13: 9783030966256
Lingua: Inglese
Da: PBShop.store US, Wood Dale, IL, U.S.A.
EUR 61,93
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Editore: Springer, Berlin|Springer International Publishing|Springer, 2023
ISBN 10: 3030966259 ISBN 13: 9783030966256
Lingua: Inglese
Da: moluna, Greven, Germania
EUR 51,51
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Aggiungi al carrelloCondizione: New.
EUR 54,99
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Aggiungi al carrelloCondizione: New.
EUR 53,86
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Aggiungi al carrelloCondizione: New. pp. 520.
EUR 51,84
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Aggiungi al carrelloPaperback or Softback. Condizione: New. Machine Learning for Text 2.23. Book.
EUR 66,64
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Aggiungi al carrelloCondizione: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
EUR 49,49
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Aggiungi al carrelloCondizione: New.
Editore: Springer International Publishing, Springer Nature Switzerland Mai 2023, 2023
ISBN 10: 3030966259 ISBN 13: 9783030966256
Lingua: Inglese
Da: Wegmann1855, Zwiesel, Germania
EUR 58,84
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware -This second edition textbook covers a coherently organized framework for text analytics, which integrates material drawn from the intersecting topics of information retrieval, machine learning, and natural language processing. Particular importance is placed on deep learning methods. The chapters of this book span three broad categories:
EUR 17,35
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Aggiungi al carrelloCondizione: Good. Exact ISBN match. Immediate shipping. No funny business.
EUR 56,29
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Aggiungi al carrelloPaperback or Softback. Condizione: New. Machine Learning for Text 1.97. Book.
EUR 15,97
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Aggiungi al carrellohardcover. Condizione: VeryGood. A copy that may have been read, very minimal wear and tear. May have a remainder mark.
EUR 62,17
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Aggiungi al carrelloCondizione: New. pp. 565.
Editore: Springer International Publishing, Springer International Publishing, 2019
ISBN 10: 3030088073 ISBN 13: 9783030088071
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 53,49
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Text analytics is a field that lies on the interface of information retrieval,machine learning, and natural language processing, and this textbookcarefully covers a coherently organized framework drawn from these intersectingtopics. The chapters of this textbook is organized into three categories:- Basic algorithms: Chapters 1 through 7 discuss the classical algorithmsfor machine learning from text such as preprocessing, similaritycomputation, topic modeling, matrix factorization, clustering,classification, regression, and ensemble analysis.- Domain-sensitive mining: Chapters 8 and 9 discuss the learning methodsfrom text when combined with different domains such as multimedia andthe Web. The problem of information retrieval and Web search is alsodiscussed in the context of its relationship with ranking and machinelearning methods.- Sequence-centric mining: Chapters 10 through 14 discuss varioussequence-centric and natural language applications, such as featureengineering, neural language models, deep learning, text summarization,information extraction, opinion mining, text segmentation, and eventdetection.This textbook covers machine learning topics for text in detail. Since thecoverage is extensive,multiple courses can be offered from the same book,depending on course level. Even though the presentation is text-centric,Chapters 3 to 7 cover machine learning algorithms that are often used indomains beyond text data. Therefore, the book can be used to offercourses not just in text analytics but also from the broader perspective ofmachine learning (with text as a backdrop).This textbook targets graduate students in computer science, as well as researchers, professors, and industrialpractitioners working in these related fields. This textbook is accompanied with a solution manual forclassroom teaching.
Editore: Springer International Publishing, Springer International Publishing Feb 2019, 2019
ISBN 10: 3030088073 ISBN 13: 9783030088071
Lingua: Inglese
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 53,49
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware -Text analytics is a field that lies on the interface of information retrieval,machine learning, and natural language processing, and this textbook carefully covers a coherently organized framework drawn from these intersecting topics. The chapters of this textbook is organized into three categories: Basic algorithms: Chapters 1 through 7 discuss the classical algorithms for machine learning from text such as preprocessing, similarity computation, topic modeling, matrix factorization, clustering, classification, regression, and ensemble analysis. Domain-sensitive mining: Chapters 8 and 9 discuss the learning methods from text when combined with different domains such as multimedia and the Web. The problem of information retrieval and Web search is also discussed in the context of its relationship with ranking and machine learning methods. Sequence-centric mining: Chapters 10 through 14 discuss various sequence-centric and natural language applications, such as feature engineering, neural language models, deep learning, text summarization, information extraction, opinion mining, text segmentation, and event detection.This textbook covers machine learning topics for text in detail. Since the coverage is extensive,multiple courses can be offered from the same book, depending on course level. Even though the presentation is text-centric, Chapters 3 to 7 cover machine learning algorithms that are often used indomains beyond text data. Therefore, the book can be used to offer courses not just in text analytics but also from the broader perspective of machine learning (with text as a backdrop).This textbook targets graduate students in computer science, as well as researchers, professors, and industrial practitioners working in these related fields. This textbook is accompanied with a solution manual for classroom teaching.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 520 pp. Englisch.
EUR 62,74
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Aggiungi al carrelloCondizione: NEW.
EUR 61,37
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Aggiungi al carrelloCondizione: New. In.
EUR 54,05
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Aggiungi al carrelloCondizione: New.
EUR 55,30
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Aggiungi al carrelloCondizione: New.
EUR 42,58
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Aggiungi al carrelloHardcover. Condizione: Good. Textbook, May Have Highlights, Notes and/or Underlining, BOOK ONLY-NO ACCESS CODE, NO CD, Ships with Emailed Tracking.
Editore: Springer International Publishing, 2023
ISBN 10: 3030966259 ISBN 13: 9783030966256
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 58,84
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This second edition textbook covers a coherently organized framework for text analytics, which integratesmaterial drawn from the intersecting topics of information retrieval, machine learning, andnatural language processing. Particular importance is placed on deep learning methods. Thechapters of this book span three broad categories:1. Basic algorithms: Chapters 1 through 7 discuss the classical algorithms for text analytics such as preprocessing, similarity computation, topic modeling, matrix factorization, clustering, classification, regression, and ensemble analysis.2. Domain-sensitive learning and information retrieval: Chapters 8 and 9 discuss learning models in heterogeneous settings such as a combination of text with multimedia or Web links. The problem of information retrieval and Web search is also discussed in the context of its relationship with ranking and machine learning methods.3. Natural language processing: Chapters 10 through 16 discuss various sequence-centric and natural language applications, such as feature engineering, neural language models, deep learning, transformers, pre-trained language models, text summarization, information extraction, knowledge graphs, question answering, opinion mining, text segmentation, and event detection.Compared to the first edition, this second edition textbook (which targets mostly advanced level students majoring in computer science and math) has substantially morematerial on deep learning and natural language processing. Significant focus isplaced on topics like transformers, pre-trained language models, knowledge graphs,and question answering.
EUR 58,05
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
EUR 58,32
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
EUR 66,86
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Aggiungi al carrelloCondizione: New. pp. 565.
Editore: Springer Nature Switzerland AG, 2022
ISBN 10: 3030966224 ISBN 13: 9783030966225
Lingua: Inglese
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 69,66
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Aggiungi al carrelloHRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.