Natural language processing : a machine learning perspective

著者

    • Zhang, Yue
    • Teng, Zhiyang

書誌事項

Natural language processing : a machine learning perspective

Yue Zhang, Zhiyang Teng

Cambridge University Press, 2021

  • : hbk

大学図書館所蔵 件 / 全5件

この図書・雑誌をさがす

注記

Includes bibliographical references (p. 453-467) and index

内容説明・目次

内容説明

With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are systematically organised by their machine learning nature, including classification, sequence labelling, and sequence-to-sequence problems. Topics covered include statistical machine learning and deep learning models, text classification and structured prediction models, generative and discriminative models, supervised and unsupervised learning with latent variables, neural networks, and transition-based methods. Rich connections are drawn between concepts throughout the book, equipping students with the tools needed to establish a deep understanding of NLP solutions, adapt existing models, and confidently develop innovative models of their own. Featuring a host of examples, intuition, and end of chapter exercises, plus sample code available as an online resource, this textbook is an invaluable tool for the upper undergraduate and graduate student.

目次

  • Part I. Basics: 1. Introduction
  • 2. Counting relative frequencies
  • 3. Feature vectors
  • 4. Discriminative linear classifiers
  • 5. A perspective from information theory
  • 6. Hidden variables
  • Part II. Structures: 7. Generative sequence labelling
  • 8. Discriminative sequence labelling
  • 9. Sequence segmentation
  • 10. Predicting tree structures
  • 11. Transition-based methods for structured prediction
  • 12. Bayesian models
  • Part III. Deep Learning: 13. Neural network
  • 14. Representation learning
  • 15. Neural structured prediction
  • 16. Working with two texts
  • 17. Pre-training and transfer learning
  • 18. Deep latent variable models
  • Index.

「Nielsen BookData」 より

詳細情報

ページトップへ