Neural machine translation
Deep learning is revolutionizing how machine translation systems are built today. This introduction to machine translation starts from the basics of neural network methods and reaches the state of the art, while giving illuminating historical, linguistic, and applied context. Code examples in Python give a hands-on blueprint for implementation.
Read More ↓Title Statements
- Full title :Neural machine translation / Philipp Koehn.
Summary
Deep learning is revolutionizing how machine translation systems are built today. This introduction to machine translation starts from the basics of neural network methods and reaches the state of the art, while giving illuminating historical, linguistic, and applied context. Code examples in Python give a hands-on blueprint for implementation.
Read More ↓Edition Statements
- Publication Date:2020.
Publication Statements
- Publisher(s):Cambridge University Press
- Place of Publication:Cambridge, United Kingdom
- Language:eng
- Publication Date:2020.
The Physical Object
- Description:xiv, 393 pages : : illustrations ; : 26 cm.
Edition Identifiers
- ISBN:9781108497329, 1108497322
- oclc:on1236021586
- Dewey Decimal:418.020285
Subjects
Writers
No reviews yet. Be the first to rate this work.
Related Works
more →
Neural networks with R: smart models using CNN, RNN, deep learn…
Ciabuschi, Francesco
Synergetics
Artificial neural networks
Neural engineering
Neural engineering
Rate & Review