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Neural Machine Translation

$69.99 (P)

  • Date Published: July 2020
  • availability: In stock
  • format: Hardback
  • isbn: 9781108497329

$ 69.99 (P)
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  • Deep learning is revolutionizing how machine translation systems are built today. This book introduces the challenge of machine translation and evaluation - including historical, linguistic, and applied context -- then develops the core deep learning methods used for natural language applications. Code examples in Python give readers a hands-on blueprint for understanding and implementing their own machine translation systems. The book also provides extensive coverage of machine learning tricks, issues involved in handling various forms of data, model enhancements, and current challenges and methods for analysis and visualization. Summaries of the current research in the field make this a state-of-the-art textbook for undergraduate and graduate classes, as well as an essential reference for researchers and developers interested in other applications of neural methods in the broader field of human language processing.

    • The first textbook on neural machine translation, with no prerequisite knowledge beyond high school math
    • Python code examples for the core methods build familiarity with implementation
    • Over 100 illustrations aid in understanding the key concepts, alongside non-technical math and an informal writing style
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    Reviews & endorsements

    ‘This book can essentially be viewed as an important contribution to the increasingly important area of neural MT, which will be a great help to NLP researchers, scientists, academics, undergraduate or postgraduate students, and MT researchers and users in particular.’ Wandri Jooste, Rejwanul Haque, and Andy Way, Machine Translation

    ‘This book can essentially be viewed as an important contribution to the increasingly important area of neural MT, which will be a great help to NLP researchers, scientists, academics, undergraduate or postgraduate students, and MT researchers and users in particular.’ Wandri Jooste, Rejwanul Haque,·Andy Way, Machine Translation

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    Product details

    • Date Published: July 2020
    • format: Hardback
    • isbn: 9781108497329
    • length: 406 pages
    • dimensions: 252 x 178 x 26 mm
    • weight: 0.84kg
    • availability: In stock
  • Table of Contents

    Part I. Introduction:
    1. The Translation Problem
    2. Uses of Machine Translation
    3. History
    4. Evaluation
    Part II. Basics:
    5. Neural Networks
    6. Computation Graphs
    7. Neural Language Models
    8. Neural Translation Models
    9. Decoding
    Part III. Refinements:
    10. Machine Learning Tricks
    11. Alternate Architectures
    12. Revisiting Words
    13. Adaptations
    14. Beyond Parallel Corpora
    15. Linguistic Structure
    16. Current Challenges
    17. Analysis and Visualization.

  • Author

    Philipp Koehn, The Johns Hopkins University
    Philipp Koehn is a leading researcher in the field of machine translation and Professor of Computer Science at Johns Hopkins University. In 2010 he authored the textbook Statistical Machine Translation (Cambridge). He received the Award of Honor from the International Association for Machine Translation and was one of three finalists for the European Inventor Award of the European Patent Office in 2013. Professor Koehn also works actively in industry as Chief Scientist for Omniscien Technology and as a consultant for Facebook.

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