Neural Machine Translation
Neural Machine Translation
$77.99
USDDeep 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
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
Product details
June 2020Adobe eBook Reader
9781108601764
0 pages
This ISBN is for an eBook version which is distributed on our behalf by a third party.
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.
