Resources#
Neural Machine Translation#
If you want to learn more about neural machine translation, check out the following resources.
Tutorials#
The Annotated Transformer by Alexander Rush
The Annotated Encoder-Decoder by Jasmijn Bastings
Graham Neubig: Neural Machine Translation and Sequence-to-sequence Models: A Tutorial.
Philipp Koehn: Neural Machine Translation.
Video recording of Chris Manning’s lecture on “NMT and Models with Attention” at Stanford (2017)
Huggingface NLP task guides: Translation
Publications#
NMT papers in the ACL anthology
statmt.org survey of NMT publications
Data#
WMT: The shared tasks of the yearly Conference on Machine Translation (WMT) provide lots of parallel data
OPUS: The OPUS project collects publicly available parallel data and provides it to everyone on their website.
Huggingface: datasets.
Toolkits#
A comprehensive list of NMT toolkits, ordered by deep learning backends can be found here.
PyTorch#
Here’s a collection of links that should help you get started or improve your coding skills with PyTorch:
Git Versioning#
Never worked with Git before? For the basics, check out this tutorial by Roger Dudler and for more advanced usage this one by Lars Vogel.