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Title: GitHub - ywu94/NLP-Notes: NLP learning notes, including classic papers, algorithm implementations, modeling tricks, and notes.

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Description: NLP learning notes, including classic papers, algorithm implementations, modeling tricks, and notes. - ywu94/NLP-Notes

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[Paper]https://github.com/ywu94/NLP-Notes/blob/master/Papers/%5BAttention%5DNeural-Machine-Translation-by-Jointly-Learning-to-Align-and-Translate.pdf
[Illustrative Intro]https://towardsdatascience.com/attn-illustrated-attention-5ec4ad276ee3
[TF2 Implementation]https://github.com/ywu94/NLP-Notes/blob/master/Implementations/add-attn-tf2implementation.py
[Paper]https://github.com/ywu94/NLP-Notes/blob/master/Papers/%5BAttention%5DEffective-Approaches-to-Attention-based-Neural-Machine-Translation.pdf
[Illustrative Intro]https://towardsdatascience.com/attn-illustrated-attention-5ec4ad276ee3
[TF2 Implementation]https://github.com/ywu94/NLP-Notes/blob/master/Implementations/mul-attn-tf2implementation.py
[Paper]https://github.com/ywu94/NLP-Notes/blob/master/Papers/%5BAttention%5DAttention-Is-All-You-Need.pdf
[Illustrative Intro]http://jalammar.github.io/illustrated-transformer/
[TF2 Implementation]https://github.com/ywu94/NLP-Notes/tree/master/Implementations/transformer-tf2implementation
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https://patch-diff.githubusercontent.com/ywu94/NLP-Notes#subword-tokenization
HuggingFace Tokenizer Summaryhttps://huggingface.co/transformers/tokenizer_summary.html
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Git Issuehttps://github.com/huggingface/transformers/issues/1083
https://patch-diff.githubusercontent.com/ywu94/NLP-Notes#industrial-application
[Paper]https://github.com/ywu94/NLP-Notes/blob/master/Papers/%5BIndustry%5DGoogle%E2%80%99s-Neural-Machine-Translation-System.pdf
[Illustrative Intro]https://towardsdatascience.com/attn-illustrated-attention-5ec4ad276ee3
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[Torch Implementation]https://github.com/ywu94/NLP-Notes/blob/master/Implementations/gnmt-torchimplementation.py
[Paper]https://github.com/ywu94/NLP-Notes/blob/master/Papers/%5BIndustry%5DBERT-Pre-training-of-Deep%20Bidirectional-Transformers-for-Language-Understanding.pdf
https://patch-diff.githubusercontent.com/ywu94/NLP-Notes#probabilistic-graph
[Introduction to CRF]https://github.com/ywu94/NLP-Notes/blob/master/Papers/%5BCRF%5DAn-Introduction-to-Conditional-Random-Field.pdf
[CRF vs MRF]https://stats.stackexchange.com/questions/156697/whats-the-difference-between-a-markov-random-field-and-a-conditional-random-fie
[CRF for Multi-label Classification]https://github.com/ywu94/NLP-Notes/blob/master/Papers/%5BCRF%5DCollective-Multi-Label-Classification.pdf
[Tensorflow CRF]https://www.tensorflow.org/addons/api_docs/python/tfa/text/crf
[Paper]https://github.com/ywu94/NLP-Notes/blob/master/Papers/%5BNER%5DNeural-Architectures-for-Named-Entity-Recognition.pdf
[TF1.0 Implementation by Scofield]https://github.com/scofield7419/sequence-labeling-BiLSTM-CRF
[Paper]https://github.com/ywu94/NLP-Notes/blob/master/Papers/%5BNER%5DHierarchically-Refined-Label-Attention-Network-for-Sequence-Labeling.pdf
[Torch Implementation by Author]https://github.com/Nealcly/BiLSTM-LAN
https://patch-diff.githubusercontent.com/ywu94/NLP-Notes#modeling-tricks
[Paper]https://arxiv.org/pdf/2002.04745.pdf
[Paper]https://ufal.mff.cuni.cz/pbml/110/art-popel-bojar.pdf
[Methodology Overview]https://mlexplained.com/2018/11/30/an-overview-of-normalization-methods-in-deep-learning/
[Layer Normalization]https://github.com/ywu94/NLP-Notes/blob/master/Papers/%5BRNN-Training%5DLayer-Normalization.pdf
[Methodology Overview]https://medium.com/@bingobee01/a-review-of-dropout-as-applied-to-rnns-72e79ecd5b7b
[Vanilla Dropout]https://github.com/ywu94/NLP-Notes/blob/master/Papers/%5BRNN-Dropout%5DRecurrent-Neural-Network-Regularization.pdf
[Variational Dropout]https://github.com/ywu94/NLP-Notes/blob/master/Papers/%5BRNN-Dropout%5DA-Theoretically-Grounded-Application-of-Dropout-in-Recurrent-Neural-Networks.pdf
[Recurrent Dropout]https://github.com/ywu94/NLP-Notes/blob/master/Papers/%5BRNN-Dropout%5DRecurrent-Dropout-without-Memory-Loss.pdf
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