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Introduction to natural language processing / Jacob Eisenstein.

By: Series: Adaptive computation and machine learningPublication details: Cambridge, Massachusetts : The MIT Press, c2019Description: xiv, 519 pages ; 24 cmISBN:
  • 9780262042840
Subject(s): DDC classification:
  • 006.35 23
LOC classification:
  • QA76.9.N38 E46 2019
Summary: "The book provides a technical perspective on the most contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. It also includes background in the salient linguistic issues, as well as computational representations and algorithms. The first section of the book explores what can be with individual words. The second section concerns structured representations such as sequences, trees, and graphs. The third section highlights different approaches to the representation and analysis of linguistic meaning. The final section describes three of the most transformative applications of natural language processing: information extraction, machine translation, and text generation. The book describes the technical foundations of the field, including the most relevant machine learning techniques, algorithms, and linguistic representations. From these foundations, it extends to contemporary research in areas such as deep learning. Each chapter contains exercises that include paper-and-pencil analysis of the computational algorithms and linguistic issues, as well as software implementations"--
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Item type Current library Home library Call number Copy number Status Date due Barcode Item holds
Book Book Ayesha Abed Library General Stacks Ayesha Abed Library General Stacks 006.35 EIS (Browse shelf(Opens below)) 1 Checked out 11/07/2024 3010037526
Book Book Ayesha Abed Library General Stacks Ayesha Abed Library General Stacks 006.35 EIS (Browse shelf(Opens below)) 2 Available 3010037527
Book Book Ayesha Abed Library General Stacks Ayesha Abed Library General Stacks 006.35 EIS (Browse shelf(Opens below)) 3 Checked out 09/07/2024 3010037528
Book Book Ayesha Abed Library General Stacks Ayesha Abed Library General Stacks 006.35 EIS (Browse shelf(Opens below)) 4 Available 3010037529
Book Book Ayesha Abed Library General Stacks Ayesha Abed Library General Stacks 006.35 EIS (Browse shelf(Opens below)) 5 Available 3010037530
Book Book Ayesha Abed Library General Stacks Ayesha Abed Library General Stacks 006.35 EIS (Browse shelf(Opens below)) 6 Checked out 15/07/2024 3010037531
Book Book Ayesha Abed Library General Stacks Ayesha Abed Library General Stacks 006.35 EIS (Browse shelf(Opens below)) 7 Available 3010037532
Book Book Ayesha Abed Library General Stacks Ayesha Abed Library General Stacks 006.35 EIS (Browse shelf(Opens below)) 8 Available 3010037533
Book Book Ayesha Abed Library General Stacks Ayesha Abed Library General Stacks 006.35 EIS (Browse shelf(Opens below)) 9 Available 3010037534
Book Book Ayesha Abed Library General Stacks Ayesha Abed Library General Stacks 006.35 EIS (Browse shelf(Opens below)) 10 Checked out 10/04/2023 3010037535
Total holds: 0

Includes bibliographical references (pages 459-508) and index.

"The book provides a technical perspective on the most contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. It also includes background in the salient linguistic issues, as well as computational representations and algorithms. The first section of the book explores what can be with individual words. The second section concerns structured representations such as sequences, trees, and graphs. The third section highlights different approaches to the representation and analysis of linguistic meaning. The final section describes three of the most transformative applications of natural language processing: information extraction, machine translation, and text generation. The book describes the technical foundations of the field, including the most relevant machine learning techniques, algorithms, and linguistic representations. From these foundations, it extends to contemporary research in areas such as deep learning. Each chapter contains exercises that include paper-and-pencil analysis of the computational algorithms and linguistic issues, as well as software implementations"--

CSE

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