Tensorflow實現的深度NLP模型集錦

 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且內部程式碼極為簡潔。

    資源整理自網路，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

標的

 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

文字分類：

 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

    完整串列包含(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

    完整串列包含(51 notebooks)

機器翻譯（英語到越南語）：

 連結：https://github.com/huseinzol05/NLP-Models-Tensorflow/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

    完整串列包含(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

物體識別：

 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-Models-Tensorflow/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

詞乾抽取：

 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 (字元識別):

 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

文字相似性:

 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

註意力機制:

 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)