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Machine Learning for Text

Produktform: Buch / Einband - fest (Hardcover)

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: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. 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.  weiterlesen

Sprache(n): Englisch

ISBN: 978-3-030-96622-5 / 978-3030966225 / 9783030966225

Verlag: Springer International Publishing

Erscheinungsdatum: 05.05.2022

Seiten: 565

Auflage: 2

Autor(en): Charu Aggarwal, Charu C. Aggarwal

80,24 € inkl. MwSt.
kostenloser Versand

lieferbar - Lieferzeit 10-15 Werktage

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