收藏 | Tensorflow實現的深度NLP模型集錦(附資源)

收集整理了一批基於Tensorflow實現的深度學習/機器學習的深度NLP模型。

基於Tensorflow的自然語言處理模型，為自然語言處理問題收集機器學習和Tensorflow深度學習模型，100%Jupeyter NoteBooks且內部代碼極為簡潔。

資源整理自網絡，源地址：

https://github.com/huseinzol05

    

目錄

Text classification

Chatbot

Neural Machine Translation

Embedded

Entity-Tagging

POS-Tagging

Dependency-Parser

Question-Answers

Supervised Summarization

Unsupervised Summarization

Stemming

Generator

Language detection

OCR (optical character recognition)

Speech to Text

Text to Speech

Text Similarity

Miscellaneous

Attention

     

目標

原始的實現稍微有點複雜，對於初學者來說有點難。所以我嘗試將其中大部分內容簡化，同時，還有很多論文的內容亟待實現，一步一步來。

內容

文本分類：

連結：

https://github.com/huseinzol05/NLP-Models-Tensorflow/tree/master/text-classification

1. Basic cell RNN

2. Bidirectional RNN

3. LSTM cell RNN

4. GRU cell RNN

5. LSTM RNN + Conv2D

6. K-max Conv1d

7. LSTM RNN + Conv1D + Highway

8. LSTM RNN with Attention

9. Neural Turing Machine

10. Seq2Seq

11. Bidirectional Transformers

12. Dynamic Memory Network

13. Residual Network using Atrous CNN + Bahdanau Attention

14. Transformer-XL

完整列表包含(66 notebooks)

聊天機器人：

連結：

https://github.com/huseinzol05/NLP-Models-Tensorflow/tree/master/chatbot

1. Seq2Seq-manual

2. Seq2Seq-API Greedy

3. Bidirectional Seq2Seq-manual

4. Bidirectional Seq2Seq-API Greedy

5. Bidirectional Seq2Seq-manual + backward Bahdanau + forward Luong

6. Bidirectional Seq2Seq-API + backward Bahdanau + forward Luong + Stack Bahdanau Luong Attention + Beam Decoder

7. Bytenet

8. Capsule layers + LSTM Seq2Seq-API + Luong Attention + Beam Decoder

9. End-to-End Memory Network

10. Attention is All you need

11. Transformer-XL + LSTM

12. GPT-2 + LSTM

完整列表包含(51 notebooks)

機器翻譯（英語到越南語）：

連結：

https://github.com/huseinzol05/NLP-ModelsTensorflow/tree/master/neural-machine-translation

1. Seq2Seq-manual

2. Seq2Seq-API Greedy

3. Bidirectional Seq2Seq-manual

4. Bidirectional Seq2Seq-API Greedy

5. Bidirectional Seq2Seq-manual + backward Bahdanau + forward Luong

6. Bidirectional Seq2Seq-API + backward Bahdanau + forward Luong + Stack Bahdanau Luong Attention + Beam Decoder

7. Bytenet

8. Capsule layers + LSTM Seq2Seq-API + Luong Attention + Beam Decoder

9. End-to-End Memory Network

10. Attention is All you need

完整列表包含(49 notebooks)

詞向量：

連結：

https://github.com/huseinzol05/NLP-Models-Tensorflow/tree/master/embedded

1. Word Vector using CBOW sample softmax

2. Word Vector using CBOW noise contrastive estimation

3. Word Vector using skipgram sample softmax

4. Word Vector using skipgram noise contrastive estimation

5. Lda2Vec Tensorflow

6. Supervised Embedded

7. Triplet-loss + LSTM

8. LSTM Auto-Encoder

9. Batch-All Triplet-loss LSTM

10. Fast-text

11. ELMO (biLM)

詞性標註：

連結：

https://github.com/huseinzol05/NLP-Models-Tensorflow/tree/master/pos-tagging

1. Bidirectional RNN + Bahdanau Attention + CRF

2. Bidirectional RNN + Luong Attention + CRF

3. Bidirectional RNN + CRF

實體識別：

連結：

https://github.com/huseinzol05/NLP-Models-Tensorflow/tree/master/entity-tagging

1. Bidirectional RNN + Bahdanau Attention + CRF

2. Bidirectional RNN + Luong Attention + CRF

3. Bidirectional RNN + CRF

4. Char Ngrams + Bidirectional RNN + Bahdanau Attention + CRF

5. Char Ngrams + Residual Network + Bahdanau Attention + CRF

依存分析：

連結：

https://github.com/huseinzol05/NLP-ModelsTensorflow/tree/master/dependency-parser

1. Bidirectional RNN + Bahdanau Attention + CRF

2. Bidirectional RNN + Luong Attention + CRF

3. Residual Network + Bahdanau Attention + CRF

4. Residual Network + Bahdanau Attention + Char Embedded + CRF

問答：

連結：

https://github.com/huseinzol05/NLP-Models-Tensorflow/tree/master/question-answer

1. End-to-End Memory Network + Basic cell

2. End-to-End Memory Network + GRU cell

3. End-to-End Memory Network + LSTM cell

詞幹抽取：

連結：

https://github.com/huseinzol05/NLP-Models-Tensorflow/tree/master/stemming

1. LSTM + Seq2Seq + Beam

2. GRU + Seq2Seq + Beam

3. LSTM + BiRNN + Seq2Seq + Beam

4. GRU + BiRNN + Seq2Seq + Beam

5. DNC + Seq2Seq + Greedy

有監督摘要抽取：

連結：

https://github.com/huseinzol05/NLP-Models-Tensorflow/tree/master/summarization

1. LSTM Seq2Seq using topic modelling

2. LSTM Seq2Seq + Luong Attention using topic modelling

3. LSTM Seq2Seq + Beam Decoder using topic modelling

4. LSTM Bidirectional + Luong Attention + Beam Decoder using topic modelling

5. LSTM Seq2Seq + Luong Attention + Pointer Generator

6. Bytenet

無監督摘要抽取:

連結：

https://github.com/huseinzol05/NLP-Models-Tensorflow/tree/master/unsupervised-summarization

1. Skip-thought Vector (unsupervised)

2. Residual Network using Atrous CNN (unsupervised)

3. Residual Network using Atrous CNN + Bahdanau Attention (unsupervised)

OCR (字符識別):

連結：

https://github.com/huseinzol05/NLP-Models-Tensorflow/tree/master/ocr

1. CNN + LSTM RNN

語音識別:

連結：

https://github.com/huseinzol05/NLP-Models-Tensorflow/tree/master/speech-to-text

1. Tacotron

2. Bidirectional RNN + Greedy CTC

3. Bidirectional RNN + Beam CTC

4. Seq2Seq + Bahdanau Attention + Beam CTC

5. Seq2Seq + Luong Attention + Beam CTC

6. Bidirectional RNN + Attention + Beam CTC

7. Wavenet

語音合成:

連結：

https://github.com/huseinzol05/NLP-Models-Tensorflow/tree/master/text-to-speech

1. Tacotron

2. Wavenet

3. Seq2Seq + Luong Attention

4. Seq2Seq + Bahdanau Attention

生成器:

連結：

https://github.com/huseinzol05/NLP-Models-Tensorflow/tree/master/generator

1. Character-wise RNN + LSTM

2. Character-wise RNN + Beam search

3. Character-wise RNN + LSTM + Embedding

4. Word-wise RNN + LSTM

5. Word-wise RNN + LSTM + Embedding

6. Character-wise + Seq2Seq + GRU

7. Word-wise + Seq2Seq + GRU

8. Character-wise RNN + LSTM + Bahdanau Attention

9. Character-wise RNN + LSTM + Luong Attention

語言檢測:

連結：

https://github.com/huseinzol05/NLP-Models-Tensorflow/tree/master/language-detection

1. Fast-text Char N-Grams

文本相似性:

連結：

https://github.com/huseinzol05/NLP-Models-Tensorflow/tree/master/text-similarity

1. Character wise similarity + LSTM + Bidirectional

2. Word wise similarity + LSTM + Bidirectional

3. Character wise similarity Triplet loss + LSTM

4. Word wise similarity Triplet loss + LSTM

注意力機制:

連結：

https://github.com/huseinzol05/NLP-Models-Tensorflow/tree/master/attention

1. Bahdanau

2. Luong

3. Hierarchical

4. Additive

5. Soft

6. Attention-over-Attention

7. Bahdanau API

8. Luong API

其他:

連結：

https://github.com/huseinzol05/NLP-Models-Tensorflow/tree/master/misc

1. Attention heatmap on Bahdanau Attention

2. Attention heatmap on Luong Attention

非深度學習：

連結：

https://github.com/huseinzol05/NLP-Models-Tensorflow/tree/master/not-deep-learning

1. Markov chatbot

2. Decomposition summarization (3 notebooks)