/nlp-tutorial

Natural Language Processing Tutorial for Deep Learning Researchers

Primary LanguageJupyter NotebookMIT LicenseMIT

nlp-tutorial

nlp-tutorial is a tutorial for who is studying NLP(Natural Language Processing) using Pytorch. Most of the models in NLP were implemented with less than 100 lines of code.(except comments or blank lines)

Dependencies

  • Python 3.6+
  • Pytorch 1.2.0+

Curriculum - (Example Purpose)

1. Basic Embedding Model

2. CNN(Convolutional Neural Network)

3. RNN(Recurrent Neural Network)

4. Attention Mechanism

5. Model based on Transformer

Model Example
NNLM Predict Next Word
Word2Vec(Softmax) Embedding Words and Show Graph
TextCNN Sentence Classification
TextRNN Predict Next Step
TextLSTM Autocomplete
Bi-LSTM Predict Next Word in Long Sentence
Seq2Seq Change Word
Seq2Seq with Attention Translate
Bi-LSTM with Attention Binary Sentiment Classification
Transformer Translate
Greedy Decoder Transformer Translate
BERT how to train

Author