Neural Machine Translation
£60.99
- Author: Philipp Koehn, The Johns Hopkins University
- Date Published: June 2020
- availability: Available
- format: Hardback
- isbn: 9781108497329
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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.
Read more- 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
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
See more reviews'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: June 2020
- format: Hardback
- isbn: 9781108497329
- length: 406 pages
- dimensions: 252 x 178 x 26 mm
- weight: 0.84kg
- availability: Available
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.
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