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https://github.com/cltdevelop/nmt#neural-machine-translation-seq2seq-tutorial
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Githubhttps://github.com/tensorflow/nmt
TensorFlow Nightlyhttps://github.com/tensorflow/tensorflow/#installation
tf-1.4https://github.com/tensorflow/nmt/tree/tf-1.4
thishttps://github.com/cltdevelop/nmt#bibtex
Introductionhttps://github.com/cltdevelop/nmt#introduction
Basichttps://github.com/cltdevelop/nmt#basic
Background on Neural Machine Translationhttps://github.com/cltdevelop/nmt#background-on-neural-machine-translation
Installing the Tutorialhttps://github.com/cltdevelop/nmt#installing-the-tutorial
Training – How to build our first NMT systemhttps://github.com/cltdevelop/nmt#training--how-to-build-our-first-nmt-system
Embeddinghttps://github.com/cltdevelop/nmt#embedding
Encoderhttps://github.com/cltdevelop/nmt#encoder
Decoderhttps://github.com/cltdevelop/nmt#decoder
Losshttps://github.com/cltdevelop/nmt#loss
Gradient computation & optimizationhttps://github.com/cltdevelop/nmt#gradient-computation--optimization
Hands-on – Let's train an NMT modelhttps://github.com/cltdevelop/nmt#hands-on--lets-train-an-nmt-model
Inference – How to generate translationshttps://github.com/cltdevelop/nmt#inference--how-to-generate-translations
Intermediatehttps://github.com/cltdevelop/nmt#intermediate
Background on the Attention Mechanismhttps://github.com/cltdevelop/nmt#background-on-the-attention-mechanism
Attention Wrapper APIhttps://github.com/cltdevelop/nmt#attention-wrapper-api
Hands-on – Building an attention-based NMT modelhttps://github.com/cltdevelop/nmt#hands-on--building-an-attention-based-nmt-model
Tips & Trickshttps://github.com/cltdevelop/nmt#tips--tricks
Building Training, Eval, and Inference Graphshttps://github.com/cltdevelop/nmt#building-training-eval-and-inference-graphs
Data Input Pipelinehttps://github.com/cltdevelop/nmt#data-input-pipeline
Other details for better NMT modelshttps://github.com/cltdevelop/nmt#other-details-for-better-nmt-models
Bidirectional RNNshttps://github.com/cltdevelop/nmt#bidirectional-rnns
Beam searchhttps://github.com/cltdevelop/nmt#beam-search
Hyperparametershttps://github.com/cltdevelop/nmt#hyperparameters
Multi-GPU traininghttps://github.com/cltdevelop/nmt#multi-gpu-training
Benchmarkshttps://github.com/cltdevelop/nmt#benchmarks
IWSLT English-Vietnamesehttps://github.com/cltdevelop/nmt#iwslt-english-vietnamese
WMT German-Englishhttps://github.com/cltdevelop/nmt#wmt-german-english
WMT English-German — Full Comparisonhttps://github.com/cltdevelop/nmt#wmt-english-german--full-comparison
Standard HParamshttps://github.com/cltdevelop/nmt#standard-hparams
Other resourceshttps://github.com/cltdevelop/nmt#other-resources
Acknowledgmenthttps://github.com/cltdevelop/nmt#acknowledgment
Referenceshttps://github.com/cltdevelop/nmt#references
BibTexhttps://github.com/cltdevelop/nmt#bibtex
https://github.com/cltdevelop/nmt#introduction
Sutskever et al., 2014https://papers.nips.cc/paper/5346-sequence-to-sequence-learning-with-neural-networks.pdf
Cho et al., 2014http://emnlp2014.org/papers/pdf/EMNLP2014179.pdf
successhttps://research.googleblog.com/2016/09/a-neural-network-for-machine.html
APIhttps://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/seq2seq/python/ops
Google’s NMT (GNMT) systemhttps://research.google.com/pubs/pub45610.html
IWSLT Evaluation Campaignhttps://sites.google.com/site/iwsltevaluation2015/
WMT Evaluation Campaignhttp://www.statmt.org/wmt16/translation-task.html
https://github.com/cltdevelop/nmt#basic
https://github.com/cltdevelop/nmt#background-on-neural-machine-translation
https://github.com/cltdevelop/nmt/blob/master/nmt/g3doc/img/encdec.jpg
"thought" vectorhttps://www.theguardian.com/science/2015/may/21/google-a-step-closer-to-developing-machines-with-human-like-intelligence
Google Neural Machine Translation systemshttps://research.googleblog.com/2016/09/a-neural-network-for-machine.html
blog posthttp://colah.github.io/posts/2015-08-Understanding-LSTMs/
Luong (2016)https://github.com/lmthang/thesis
https://github.com/cltdevelop/nmt/blob/master/nmt/g3doc/img/seq2seq.jpg
https://github.com/cltdevelop/nmt#installing-the-tutorial
installation instructions herehttps://www.tensorflow.org/install/
https://github.com/cltdevelop/nmt#training--how-to-build-our-first-nmt-system
model.pyhttps://github.com/cltdevelop/nmt/blob/master/nmt/model.py
https://github.com/cltdevelop/nmt#embedding
https://github.com/cltdevelop/nmt#encoder
https://github.com/cltdevelop/nmt#decoder
helper.pyhttps://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/seq2seq/python/ops/helper.py
https://github.com/cltdevelop/nmt#loss
https://github.com/cltdevelop/nmt#gradient-computation--optimization
benchmarkshttps://github.com/cltdevelop/nmt#benchmarks
https://github.com/cltdevelop/nmt#hands-on--lets-train-an-nmt-model
nmt.pyhttps://github.com/cltdevelop/nmt/blob/master/nmt/nmt.py
https://nlp.stanford.edu/projects/nmt/https://nlp.stanford.edu/projects/nmt/
train.pyhttps://github.com/cltdevelop/nmt/blob/master/nmt/train.py
https://github.com/cltdevelop/nmt#inference--how-to-generate-translations
https://github.com/cltdevelop/nmt/blob/master/nmt/g3doc/img/greedy_dec.jpg
inference.pyhttps://github.com/cltdevelop/nmt/blob/master/nmt/inference.py
https://github.com/cltdevelop/nmt#intermediate
Bahdanau et al., 2015https://arxiv.org/abs/1409.0473
Luong et al., 2015https://arxiv.org/abs/1508.04025
https://github.com/cltdevelop/nmt/blob/master/nmt/g3doc/img/attention_vis.jpg
https://github.com/cltdevelop/nmt#background-on-the-attention-mechanism
OpenNMThttp://opennmt.net/about/
https://github.com/cltdevelop/nmt/blob/master/nmt/g3doc/img/attention_mechanism.jpg
https://github.com/cltdevelop/nmt/blob/master/nmt/g3doc/img/attention_equation_0.jpg
https://github.com/cltdevelop/nmt/blob/master/nmt/g3doc/img/attention_equation_1.jpg
attention_wrapper.pyhttps://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/seq2seq/python/ops/attention_wrapper.py
benchmark resultshttps://github.com/cltdevelop/nmt#benchmarks
https://github.com/cltdevelop/nmt#attention-wrapper-api
AttentionWrapperhttps://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/seq2seq/python/ops/attention_wrapper.py
(Weston et al., 2015)https://arxiv.org/abs/1410.3916
attention_model.pyhttps://github.com/cltdevelop/nmt/blob/master/nmt/attention_model.py
Encoderhttps://github.com/cltdevelop/nmt#encoder
Decoderhttps://github.com/cltdevelop/nmt#decoder
https://github.com/cltdevelop/nmt#hands-on--building-an-attention-based-nmt-model
https://github.com/cltdevelop/nmt#tips--tricks
https://github.com/cltdevelop/nmt#building-training-eval-and-inference-graphs
https://github.com/cltdevelop/nmt#data-input-pipeline
utils/iterator_utils.pyhttps://github.com/cltdevelop/nmt/blob/master/nmt/utils/iterator_utils.py
https://github.com/cltdevelop/nmt#other-details-for-better-nmt-models
https://github.com/cltdevelop/nmt#bidirectional-rnns
model.pyhttps://github.com/cltdevelop/nmt/blob/master/nmt/model.py
https://github.com/cltdevelop/nmt#beam-search
Neubig, (2017)https://arxiv.org/abs/1703.01619
Decoderhttps://github.com/cltdevelop/nmt#decoder
model.pyhttps://github.com/cltdevelop/nmt/blob/master/nmt/model.py
https://github.com/cltdevelop/nmt#hyperparameters
https://github.com/cltdevelop/nmt#multi-gpu-training
GNMT attention architecturehttps://arxiv.org/pdf/1609.08144.pdf
GNMTAttentionMultiCellhttps://github.com/cltdevelop/nmt/blob/master/nmt/gnmt_model.py
https://github.com/cltdevelop/nmt#benchmarks
https://github.com/cltdevelop/nmt#iwslt-english-vietnamese
download scripthttps://github.com/cltdevelop/nmt/blob/master/nmt/scripts/download_iwslt15.sh
model 1http://download.tensorflow.org/models/nmt/envi_model_1.zip
model 2http://download.tensorflow.org/models/nmt/envi_model_2.zip
(Papineni et al., 2002)http://www.aclweb.org/anthology/P02-1040.pdf
(Luong & Manning, 2015)https://nlp.stanford.edu/pubs/luong-manning-iwslt15.pdf
https://github.com/cltdevelop/nmt#wmt-german-english
download scripthttps://github.com/cltdevelop/nmt/blob/master/nmt/scripts/wmt16_en_de.sh
BPEhttps://github.com/rsennrich/subword-nmt
model 1http://download.tensorflow.org/models/nmt/deen_model_1.zip
model 2http://download.tensorflow.org/models/nmt/deen_model_2.zip
modelhttp://download.tensorflow.org/models/nmt/10122017/deen_gnmt_model_4_layer.zip
WMT SOTAhttp://matrix.statmt.org/
https://github.com/cltdevelop/nmt#wmt-english-german--full-comparison
model 1 (4 layers)http://download.tensorflow.org/models/nmt/10122017/ende_gnmt_model_4_layer.zip
model 2 (8 layers)http://download.tensorflow.org/models/nmt/10122017/ende_gnmt_model_8_layer.zip
WMT SOTAhttp://matrix.statmt.org/
(Klein et al., 2017)https://arxiv.org/abs/1701.02810
(Britz et al., 2017)https://arxiv.org/abs/1703.03906
(Wu et al., 2016)https://research.google.com/pubs/pub45610.html
(Vaswani et al., 2017)https://arxiv.org/abs/1706.03762
https://github.com/cltdevelop/nmt#standard-hparams
a set of standard hparamshttps://github.com/cltdevelop/nmt/blob/master/nmt/standard_hparams
https://github.com/cltdevelop/nmt#other-resources
Luong, Cho, Manning, (2016)https://sites.google.com/site/acl16nmt/
Luong, (2016)https://github.com/lmthang/thesis
Neubig, (2017)https://arxiv.org/abs/1703.01619
https://nlp.stanford.edu/projects/nmt/https://nlp.stanford.edu/projects/nmt/
https://github.com/google/seq2seqhttps://github.com/google/seq2seq
https://github.com/rsennrich/nematushttps://github.com/rsennrich/nematus
http://opennmt.net/http://opennmt.net/
https://github.com/OpenNMT/OpenNMT-pyhttps://github.com/OpenNMT/OpenNMT-py
https://github.com/cltdevelop/nmt#acknowledgment
https://github.com/cltdevelop/nmt#references
Neural machine translation by jointly learning to align and translatehttps://arxiv.org/pdf/1409.0473.pdf
Effective approaches to attention-based neural machine translationhttps://arxiv.org/pdf/1508.04025.pdf
Sequence to sequence learning with neural networkshttps://papers.nips.cc/paper/5346-sequence-to-sequence-learning-with-neural-networks.pdf
https://github.com/cltdevelop/nmt#bibtex
Readme https://github.com/cltdevelop/nmt#readme-ov-file
Apache-2.0 license https://github.com/cltdevelop/nmt#Apache-2.0-1-ov-file
Contributing https://github.com/cltdevelop/nmt#contributing-ov-file
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