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
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
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)