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Title: GitHub - flyskywen/NLP_ability: 总结梳理自然语言处理工程师(NLP)需要积累的各方面知识，包括面试题，各种基础知识，工程能力等等，提升核心竞争力 · GitHub

Open Graph Title: GitHub - flyskywen/NLP_ability: 总结梳理自然语言处理工程师(NLP)需要积累的各方面知识，包括面试题，各种基础知识，工程能力等等，提升核心竞争力

X Title: GitHub - flyskywen/NLP_ability: 总结梳理自然语言处理工程师(NLP)需要积累的各方面知识，包括面试题，各种基础知识，工程能力等等，提升核心竞争力

Description: 总结梳理自然语言处理工程师(NLP)需要积累的各方面知识，包括面试题，各种基础知识，工程能力等等，提升核心竞争力 - flyskywen/NLP_ability

Open Graph Description: 总结梳理自然语言处理工程师(NLP)需要积累的各方面知识，包括面试题，各种基础知识，工程能力等等，提升核心竞争力 - flyskywen/NLP_ability

X Description: 总结梳理自然语言处理工程师(NLP)需要积累的各方面知识，包括面试题，各种基础知识，工程能力等等，提升核心竞争力 - flyskywen/NLP_ability

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https://github.com/flyskywen/NLP_ability#深度学习自然语言处理
https://github.com/flyskywen/NLP_ability#transformer
史上最全Transformer面试题https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Transformer/%E5%8F%B2%E4%B8%8A%E6%9C%80%E5%85%A8Transformer%E9%9D%A2%E8%AF%95%E9%A2%98.md
答案解析(1)-史上最全Transformer面试题https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Transformer/%E7%AD%94%E6%A1%88%E8%A7%A3%E6%9E%90(1)%E2%80%94%E5%8F%B2%E4%B8%8A%E6%9C%80%E5%85%A8Transformer%E9%9D%A2%E8%AF%95%E9%A2%98%EF%BC%9A%E7%81%B5%E9%AD%8220%E9%97%AE%E5%B8%AE%E4%BD%A0%E5%BD%BB%E5%BA%95%E6%90%9E%E5%AE%9ATransformer.md
Pytorch代码分析--如何让Bert在finetune小数据集时更“稳”一点https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert/Pytorch%E4%BB%A3%E7%A0%81%E5%88%86%E6%9E%90-%E5%A6%82%E4%BD%95%E8%AE%A9Bert%E5%9C%A8finetune%E5%B0%8F%E6%95%B0%E6%8D%AE%E9%9B%86%E6%97%B6%E6%9B%B4%E2%80%9C%E7%A8%B3%E2%80%9D%E4%B8%80%E7%82%B9.md
解决老大难问题-如何一行代码带你随心所欲重新初始化bert的某些参数(附Pytorch代码详细解读)https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert/%E8%A7%A3%E5%86%B3%E8%80%81%E5%A4%A7%E9%9A%BE%E9%97%AE%E9%A2%98-%E5%A6%82%E4%BD%95%E4%B8%80%E8%A1%8C%E4%BB%A3%E7%A0%81%E5%B8%A6%E4%BD%A0%E9%9A%8F%E5%BF%83%E6%89%80%E6%AC%B2%E9%87%8D%E6%96%B0%E5%88%9D%E5%A7%8B%E5%8C%96bert%E7%9A%84%E6%9F%90%E4%BA%9B%E5%8F%82%E6%95%B0(%E9%99%84Pytorch%E4%BB%A3%E7%A0%81).md
3分钟从零解读Transformer的Encoderhttps://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Transformer/3%E5%88%86%E9%92%9F%E4%BB%8E%E9%9B%B6%E8%A7%A3%E8%AF%BBTransformer%E7%9A%84Encoder.md
原版Transformer的位置编码究竟有没有包含相对位置信息https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Transformer/%E5%8E%9F%E7%89%88Transformer%E7%9A%84%E4%BD%8D%E7%BD%AE%E7%BC%96%E7%A0%81%E7%A9%B6%E7%AB%9F%E6%9C%89%E6%B2%A1%E6%9C%89%E5%8C%85%E5%90%AB%E7%9B%B8%E5%AF%B9%E4%BD%8D%E7%BD%AE%E4%BF%A1%E6%81%AF.md
BN踩坑记--谈一下Batch Normalization的优缺点和适用场景https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Transformer/BN%E8%B8%A9%E5%9D%91%E8%AE%B0--%E8%B0%88%E4%B8%80%E4%B8%8BBatch%20Normalization%E7%9A%84%E4%BC%98%E7%BC%BA%E7%82%B9%E5%92%8C%E9%80%82%E7%94%A8%E5%9C%BA%E6%99%AF.md
谈一下相对位置编码https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Transformer/%E8%B0%88%E4%B8%80%E4%B8%8B%E7%9B%B8%E5%AF%B9%E4%BD%8D%E7%BD%AE%E7%BC%96%E7%A0%81.md
NLP任务中-layer-norm比BatchNorm好在哪里https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Transformer/NLP%E4%BB%BB%E5%8A%A1%E4%B8%AD-layer-norm%E6%AF%94BatchNorm%E5%A5%BD%E5%9C%A8%E5%93%AA%E9%87%8C.md
谈一谈Decoder模块https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Transformer/%E8%B0%88%E4%B8%80%E8%B0%88Decoder%E6%A8%A1%E5%9D%97.md
Transformer的并行化https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Transformer/Transformer%E7%9A%84%E5%B9%B6%E8%A1%8C%E5%8C%96.md
Transformer全部文章合辑https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Transformer/%E7%AD%94%E6%A1%88%E5%90%88%E8%BE%91.md
RNN的梯度消失有什么与众不同的地方.mdhttps://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E5%85%B6%E4%BB%96/RNN%E7%9A%84%E6%A2%AF%E5%BA%A6%E6%B6%88%E5%A4%B1%E6%9C%89%E4%BB%80%E4%B9%88%E4%B8%8E%E4%BC%97%E4%B8%8D%E5%90%8C%E7%9A%84%E5%9C%B0%E6%96%B9.md
VIT-如何将Transformer更好的应用到CV领域https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Transformer/VIT-%E5%A6%82%E4%BD%95%E5%B0%86Transformer%E6%9B%B4%E5%A5%BD%E7%9A%84%E5%BA%94%E7%94%A8%E5%88%B0CV%E9%A2%86%E5%9F%9F.md
https://github.com/flyskywen/NLP_ability#bert-基本知识
FastBERT-CPU推理加速10倍https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert/FastBert.md
RoBERTa：更多更大更强https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert/RoBERTa.md
为什么Bert做不好无监督语义匹配https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert/%E4%B8%BA%E4%BB%80%E4%B9%88Bert%E5%81%9A%E4%B8%8D%E5%A5%BD%E6%97%A0%E7%9B%91%E7%9D%A3%E8%AF%AD%E4%B9%89%E5%8C%B9%E9%85%8D.md
UniLM:为Bert插上文本生成的翅膀https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert/UniLM.md
tBERT-BERT融合主题模型做文本匹配https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert/tBERT-BERT%E8%9E%8D%E5%90%88%E4%B8%BB%E9%A2%98%E6%A8%A1%E5%9E%8B.md
XLNET模型从零解读https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert/XLNET.md
如何在脱敏数据中使用BERT等预训练模型https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/BERT/%E5%A6%82%E4%BD%95%E5%9C%A8%E8%84%B1%E6%95%8F%E6%95%B0%E6%8D%AE%E4%B8%AD%E4%BD%BF%E7%94%A8BERT%E7%AD%89%E9%A2%84%E8%AE%AD%E7%BB%83%E6%A8%A1%E5%9E%8B.md
https://github.com/flyskywen/NLP_ability#bert-知识蒸馏
什么是知识蒸馏https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%A8%A1%E5%9E%8B%E8%92%B8%E9%A6%8F/%E4%BB%80%E4%B9%88%E6%98%AF%E7%9F%A5%E8%AF%86%E8%92%B8%E9%A6%8F.md
如何让 TextCNN 逼近 Berthttps://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%A8%A1%E5%9E%8B%E8%92%B8%E9%A6%8F/bert2textcnn%E6%A8%A1%E5%9E%8B%E8%92%B8%E9%A6%8F.md
Bert蒸馏到简单网络lstmhttps://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%A8%A1%E5%9E%8B%E8%92%B8%E9%A6%8F/Bert%E8%92%B8%E9%A6%8F%E5%88%B0%E7%AE%80%E5%8D%95%E7%BD%91%E7%BB%9Clstm.md
PKD-Bert基于多层的知识蒸馏方式https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%A8%A1%E5%9E%8B%E8%92%B8%E9%A6%8F/PKD-Bert%E5%9F%BA%E4%BA%8E%E5%A4%9A%E5%B1%82%E7%9A%84%E7%9F%A5%E8%AF%86%E8%92%B8%E9%A6%8F%E6%96%B9%E5%BC%8F.md
BERT-of-Theseus-模块压缩交替训练https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%A8%A1%E5%9E%8B%E8%92%B8%E9%A6%8F/Theseus-%E6%A8%A1%E5%9D%97%E5%8E%8B%E7%BC%A9%E4%BA%A4%E6%9B%BF%E8%AE%AD%E7%BB%83.md
tinybert-全方位蒸馏https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%A8%A1%E5%9E%8B%E8%92%B8%E9%A6%8F/tinybert-%E5%85%A8%E6%96%B9%E4%BD%8D%E8%92%B8%E9%A6%8F.md
ALBERT：更小更少但并不快https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%A8%A1%E5%9E%8B%E8%92%B8%E9%A6%8F/ALBERT-%E6%9B%B4%E5%B0%8F%E6%9B%B4%E5%B0%91%E4%BD%86%E5%B9%B6%E4%B8%8D%E5%BF%AB.md
BERT知识蒸馏代码解析-如何写好损失函数https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%A8%A1%E5%9E%8B%E8%92%B8%E9%A6%8F/BERT%E7%9F%A5%E8%AF%86%E8%92%B8%E9%A6%8F%E4%BB%A3%E7%A0%81%E8%A7%A3%E6%9E%90-%E5%A6%82%E4%BD%95%E5%86%99%E5%A5%BD%E6%8D%9F%E5%A4%B1%E5%87%BD%E6%95%B0.md
知识蒸馏综述万字长文https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%A8%A1%E5%9E%8B%E8%92%B8%E9%A6%8F/%E7%9F%A5%E8%AF%86%E8%92%B8%E9%A6%8F%E7%BB%BC%E8%BF%B0%E4%B8%87%E5%AD%97%E9%95%BF%E6%96%87.md
https://github.com/flyskywen/NLP_ability#词向量-word-embedding
史上最全词向量面试题-Word2vec/fasttext/glove/Elmohttps://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E8%AF%8D%E5%90%91%E9%87%8F/%E5%8F%B2%E4%B8%8A%E6%9C%80%E5%85%A8%E8%AF%8D%E5%90%91%E9%87%8F%E9%9D%A2%E8%AF%95%E9%A2%98%E6%A2%B3%E7%90%86.md
Word2vec两种训练模型详细解读-一个词经过模型训练可以获得几个词向量https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E8%AF%8D%E5%90%91%E9%87%8F/%E8%81%8A%E4%B8%80%E4%B8%8BWord2vec-%E6%A8%A1%E5%9E%8B%E7%AF%87.md
Word2vec两种优化方式细节详细解读https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E8%AF%8D%E5%90%91%E9%87%8F/%E8%81%8A%E4%B8%80%E4%B8%8BWord2vec-%E8%AE%AD%E7%BB%83%E4%BC%98%E5%8C%96%E7%AF%87.md
Word2vec-负采样和层序softmax与原模型是否等价https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E8%AF%8D%E5%90%91%E9%87%8F/word2vec%E4%B8%A4%E7%A7%8D%E4%BC%98%E5%8C%96%E6%96%B9%E5%BC%8F%E7%9A%84%E8%81%94%E7%B3%BB%E5%92%8C%E5%8C%BA%E5%88%AB.md
Word2vec为何需要二次采样以及相关细节详细解读https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E8%AF%8D%E5%90%91%E9%87%8F/Word2vec%E4%B8%BA%E4%BB%80%E4%B9%88%E9%9C%80%E8%A6%81%E4%BA%8C%E6%AC%A1%E9%87%87%E6%A0%B7%EF%BC%9F.md
Word2vec的负采样https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E8%AF%8D%E5%90%91%E9%87%8F/Word2vec%E7%9A%84%E8%B4%9F%E9%87%87%E6%A0%B7.md
Word2vec模型究竟是如何获得词向量的https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E8%AF%8D%E5%90%91%E9%87%8F/Word2vec%E6%A8%A1%E5%9E%8B%E7%A9%B6%E7%AB%9F%E6%98%AF%E5%A6%82%E4%BD%95%E8%8E%B7%E5%BE%97%E8%AF%8D%E5%90%91%E9%87%8F%E7%9A%84.md
Word2vec训练参数的选定https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E8%AF%8D%E5%90%91%E9%87%8F/Word2vec%E8%AE%AD%E7%BB%83%E5%8F%82%E6%95%B0%E7%9A%84%E9%80%89%E5%AE%9A.md
CBOW和skip-gram相较而言，彼此相对适合哪些场景.mdhttps://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E8%AF%8D%E5%90%91%E9%87%8F/CBOW%E5%92%8Cskip-gram%E7%9B%B8%E8%BE%83%E8%80%8C%E8%A8%80%EF%BC%8C%E5%BD%BC%E6%AD%A4%E7%9B%B8%E5%AF%B9%E9%80%82%E5%90%88%E5%93%AA%E4%BA%9B%E5%9C%BA%E6%99%AF.md
Fasttext详解解读(1)-文本分类https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E8%AF%8D%E5%90%91%E9%87%8F/Fasttext%E8%A7%A3%E8%AF%BB(1).md
Fasttext详解解读(2)-训练词向量https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E8%AF%8D%E5%90%91%E9%87%8F/Fasttext%E8%A7%A3%E8%AF%BB(2).md
GLove细节详细解读https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E8%AF%8D%E5%90%91%E9%87%8F/%E8%81%8A%E4%B8%80%E4%B8%8BGlove.md
https://github.com/flyskywen/NLP_ability#多模态
多模态之ViLBERT：双流网络，各自为王https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E5%A4%9A%E6%A8%A1%E6%80%81/%E5%A4%9A%E6%A8%A1%E6%80%81%E4%B9%8BViLBERT%EF%BC%9A%E5%8F%8C%E6%B5%81%E7%BD%91%E7%BB%9C%EF%BC%8C%E5%90%84%E8%87%AA%E4%B8%BA%E7%8E%8B.md
复盘多模态任务落地的六大问题https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E5%A4%9A%E6%A8%A1%E6%80%81/%E5%A4%8D%E7%9B%98%E5%A4%9A%E6%A8%A1%E6%80%81%E9%9C%80%E8%A6%81%E8%A7%A3%E5%86%B3%E7%9A%846%E4%B8%AA%E9%97%AE%E9%A2%98.md
如何将多模态数据融入到BERT架构中-多模态BERT的两类预训练任务https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E5%A4%9A%E6%A8%A1%E6%80%81/%E5%A6%82%E4%BD%95%E5%B0%86%E5%A4%9A%E6%A8%A1%E6%80%81%E6%95%B0%E6%8D%AE%E8%9E%8D%E5%85%A5%E5%88%B0BERT%E6%9E%B6%E6%9E%84%E4%B8%AD-%E5%A4%9A%E6%A8%A1%E6%80%81BERT%E7%9A%84%E4%B8%A4%E7%B1%BB%E9%A2%84%E8%AE%AD%E7%BB%83%E4%BB%BB%E5%8A%A1.md
层次分类体系的必要性-多模态讲解系列(1)https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E5%A4%9A%E6%A8%A1%E6%80%81/%E5%B1%82%E6%AC%A1%E5%88%86%E7%B1%BB%E4%BD%93%E7%B3%BB%E7%9A%84%E5%BF%85%E8%A6%81%E6%80%A7-%E5%A4%9A%E6%A8%A1%E6%80%81%E8%AE%B2%E8%A7%A3%E7%B3%BB%E5%88%97.md
文本和图像特征表示模块详解-多模态讲解系列(2)https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E5%A4%9A%E6%A8%A1%E6%80%81/%E6%96%87%E6%9C%AC%E5%92%8C%E5%9B%BE%E5%83%8F%E7%89%B9%E5%BE%81%E8%A1%A8%E7%A4%BA%E6%A8%A1%E5%9D%97%E8%AF%A6%E8%A7%A3-%E5%A4%9A%E6%A8%A1%E6%80%81%E8%AE%B2%E8%A7%A3%E7%B3%BB%E5%88%97.md
多模态中各种Fusion方式汇总https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E5%A4%9A%E6%A8%A1%E6%80%81/%E5%A4%9A%E6%A8%A1%E6%80%81%E4%B8%AD%E5%90%84%E7%A7%8DFusion%E6%96%B9%E5%BC%8F%E6%B1%87%E6%80%BB.md
https://github.com/flyskywen/NLP_ability#句向量-sentence-embedding
句向量模型综述https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E5%8F%A5%E5%90%91%E9%87%8F/%E5%8F%A5%E5%90%91%E9%87%8F%E6%A8%A1%E5%9E%8B%E7%BB%BC%E8%BF%B0.md
https://github.com/flyskywen/NLP_ability#文本相似度
五千字全面梳理文本相似度/文本匹配模型https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%96%87%E6%9C%AC%E5%8C%B9%E9%85%8D%E5%92%8C%E6%96%87%E6%9C%AC%E7%9B%B8%E4%BC%BC%E5%BA%A6/%E4%BA%94%E5%8D%83%E5%AD%97%E5%85%A8%E9%9D%A2%E6%A2%B3%E7%90%86%E6%96%87%E6%9C%AC%E7%9B%B8%E4%BC%BC%E5%BA%A6%E5%92%8C%E6%96%87%E6%9C%AC%E5%8C%B9%E9%85%8D%E6%A8%A1%E5%9E%8B.md
如何又好又快的做文本匹配-ESIM模型https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%96%87%E6%9C%AC%E5%8C%B9%E9%85%8D%E5%92%8C%E6%96%87%E6%9C%AC%E7%9B%B8%E4%BC%BC%E5%BA%A6/ESIM.md
阿里RE2-将残差连接和文本匹配模型融合.mdhttps://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%96%87%E6%9C%AC%E5%8C%B9%E9%85%8D%E5%92%8C%E6%96%87%E6%9C%AC%E7%9B%B8%E4%BC%BC%E5%BA%A6/%E9%98%BF%E9%87%8CRE2-%E5%B0%86%E6%AE%8B%E5%B7%AE%E8%BF%9E%E6%8E%A5%E5%92%8C%E6%96%87%E6%9C%AC%E5%8C%B9%E9%85%8D%E6%A8%A1%E5%9E%8B%E8%9E%8D%E5%90%88.md
聊一下孪生网络和DSSM的混淆点以及向量召回的一个细节https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%96%87%E6%9C%AC%E5%8C%B9%E9%85%8D%E5%92%8C%E6%96%87%E6%9C%AC%E7%9B%B8%E4%BC%BC%E5%BA%A6/%E8%81%8A%E4%B8%80%E4%B8%8B%E5%AD%AA%E7%94%9F%E7%BD%91%E7%BB%9C%E5%92%8CDSSM%E7%9A%84%E6%B7%B7%E6%B7%86%E7%82%B9%E4%BB%A5%E5%8F%8A%E5%90%91%E9%87%8F%E5%8F%AC%E5%9B%9E%E7%9A%84%E4%B8%80%E4%B8%AA%E7%BB%86%E8%8A%82.md
DSSM论文-公司实战文章https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%96%87%E6%9C%AC%E5%8C%B9%E9%85%8D%E5%92%8C%E6%96%87%E6%9C%AC%E7%9B%B8%E4%BC%BC%E5%BA%A6/DSSM%E8%AE%BA%E6%96%87-%E5%85%AC%E5%8F%B8%E5%AE%9E%E6%88%98%E6%96%87%E7%AB%A0.md
bert白化简单的梳理:公式推导+PCA&SVD+代码解读https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%96%87%E6%9C%AC%E5%8C%B9%E9%85%8D%E5%92%8C%E6%96%87%E6%9C%AC%E7%9B%B8%E4%BC%BC%E5%BA%A6/bert%E7%99%BD%E5%8C%96%E7%AE%80%E5%8D%95%E7%9A%84%E6%A2%B3%E7%90%86.md
SIMCSE论文解析https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%96%87%E6%9C%AC%E5%8C%B9%E9%85%8D%E5%92%8C%E6%96%87%E6%9C%AC%E7%9B%B8%E4%BC%BC%E5%BA%A6/SIMCSE%E8%AE%BA%E6%96%87%E8%A7%A3%E6%9E%90.md
https://github.com/flyskywen/NLP_ability#关键词提取
基于词典的正向/逆向最大匹配https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E5%85%B3%E9%94%AE%E8%AF%8D%E6%8F%90%E5%8F%96/%E4%B8%AD%E6%96%87%E5%88%86%E8%AF%8D/%E5%9F%BA%E4%BA%8E%E8%AF%8D%E5%85%B8%E7%9A%84%E6%AD%A3%E5%90%91%E6%9C%80%E5%A4%A7%E5%8C%B9%E9%85%8D%E5%92%8C%E9%80%86%E5%90%91%E6%9C%80%E5%A4%A7%E5%8C%B9%E9%85%8D%E4%B8%AD%E6%96%87%E5%88%86%E8%AF%8D.md
实体库构建：大规模离线新词实体挖掘https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E5%85%B3%E9%94%AE%E8%AF%8D%E6%8F%90%E5%8F%96/%E5%AE%9E%E4%BD%93%E5%BA%93%E6%9E%84%E5%BB%BA%EF%BC%9A%E5%A4%A7%E8%A7%84%E6%A8%A1%E7%A6%BB%E7%BA%BF%E6%96%B0%E8%AF%8D%E5%AE%9E%E4%BD%93%E6%8C%96%E6%8E%98.md
聊一聊NLPer如何做关键词抽取https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E5%85%B3%E9%94%AE%E8%AF%8D%E6%8F%90%E5%8F%96/%E5%85%B3%E9%94%AE%E8%AF%8D%E6%8F%90%E5%8F%96%E6%96%B9%E6%B3%95%E7%BB%BC%E8%BF%B0.md
https://github.com/flyskywen/NLP_ability#命名体识别
命名体识别资源梳理(代码+博客讲解)https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E5%91%BD%E5%90%8D%E4%BD%93%E8%AF%86%E5%88%AB/%E5%91%BD%E5%90%8D%E4%BD%93%E8%AF%86%E5%88%AB%E8%B5%84%E6%BA%90%E6%A2%B3%E7%90%86(%E4%BB%A3%E7%A0%81%2B%E5%8D%9A%E5%AE%A2%E8%AE%B2%E8%A7%A3).md
HMM/CRF 详细解读https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E5%91%BD%E5%90%8D%E4%BD%93%E8%AF%86%E5%88%AB/HMM_CRF.md
工业级命名体识别的做法https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E5%91%BD%E5%90%8D%E4%BD%93%E8%AF%86%E5%88%AB/%E5%B7%A5%E4%B8%9A%E7%BA%A7%E5%91%BD%E5%90%8D%E4%BD%93%E8%AF%86%E5%88%AB%E7%9A%84%E5%81%9A%E6%B3%95.md
词典匹配+模型预测-实体识别两大法宝https://github.com/DA-southampton/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E5%91%BD%E5%90%8D%E4%BD%93%E8%AF%86%E5%88%AB/%E8%AF%8D%E5%85%B8%E5%8C%B9%E9%85%8D%2B%E6%A8%A1%E5%9E%8B%E9%A2%84%E6%B5%8B-%E5%AE%9E%E4%BD%93%E8%AF%86%E5%88%AB%E4%B8%A4%E5%A4%A7%E6%B3%95%E5%AE%9D.md
autoner+fuzzy-CRF-使用领域词典做命名体识别https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E5%91%BD%E5%90%8D%E4%BD%93%E8%AF%86%E5%88%AB/autoner.md
FLAT-Transformer-词典+Transformer融合词汇信息https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E5%91%BD%E5%90%8D%E4%BD%93%E8%AF%86%E5%88%AB/FLAT-Transformer.md
TENER-复旦为什么TRM在NER上效果差.mdhttps://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E5%91%BD%E5%90%8D%E4%BD%93%E8%AF%86%E5%88%AB/TNER-%E5%A4%8D%E6%97%A6%E4%B8%BA%E4%BB%80%E4%B9%88TRM%E5%9C%A8NER%E4%B8%8A%E6%95%88%E6%9E%9C%E5%B7%AE.md
https://github.com/flyskywen/NLP_ability#文本分类
TextCNN论文详细解读https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%96%87%E6%9C%AC%E5%88%86%E7%B1%BB/CNN%E6%96%87%E6%9C%AC%E5%88%86%E7%B1%BB%E8%A7%A3%E8%AF%BB.md
只使用标签名称就可以文本分类.md https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%96%87%E6%9C%AC%E5%88%86%E7%B1%BB/%E5%8F%AA%E4%BD%BF%E7%94%A8%E6%A0%87%E7%AD%BE%E5%90%8D%E7%A7%B0%E5%B0%B1%E5%8F%AF%E4%BB%A5%E6%96%87%E6%9C%AC%E5%88%86%E7%B1%BB.md
半监督入门思想之伪标签https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%96%87%E6%9C%AC%E5%88%86%E7%B1%BB/%E5%8D%8A%E7%9B%91%E7%9D%A3%E5%85%A5%E9%97%A8%E6%80%9D%E6%83%B3%E4%B9%8B%E4%BC%AA%E6%A0%87%E7%AD%BE.md
ACL2020-多任务负监督方式增加CLS表达差异性https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%96%87%E6%9C%AC%E5%88%86%E7%B1%BB/ACL2020-%E5%A4%9A%E4%BB%BB%E5%8A%A1%E8%B4%9F%E7%9B%91%E7%9D%A3%E6%96%B9%E5%BC%8F%E5%A2%9E%E5%8A%A0CLS%E8%A1%A8%E8%BE%BE%E5%B7%AE%E5%BC%82%E6%80%A7.md
Bert在文本分类任务上微调https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%96%87%E6%9C%AC%E5%88%86%E7%B1%BB/%E5%9C%A8%E6%96%87%E6%9C%AC%E5%88%86%E7%B1%BB%E4%B8%8A%E5%BE%AE%E8%B0%83Bert.md
UDA-Unsupervised Data Augmentation for Consistency Training-半监督集大成https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%96%87%E6%9C%AC%E5%88%86%E7%B1%BB/UDA.md
LCM-缓解标签不独立以及标注错误的问题https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%96%87%E6%9C%AC%E5%88%86%E7%B1%BB/LCM-%E7%BC%93%E8%A7%A3%E6%A0%87%E7%AD%BE%E4%B8%8D%E7%8B%AC%E7%AB%8B%E4%BB%A5%E5%8F%8A%E6%A0%87%E6%B3%A8%E9%94%99%E8%AF%AF%E7%9A%84%E9%97%AE%E9%A2%98.md
关键词信息如何融入到文本分类任务中https://github.com/flyskywen/NLP_ability/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%96%87%E6%9C%AC%E5%88%86%E7%B1%BB/%E5%85%B3%E9%94%AE%E8%AF%8D%E4%BF%A1%E6%81%AF%E5%A6%82%E4%BD%95%E8%9E%8D%E5%85%A5%E5%88%B0%E6%96%87%E6%9C%AC%E5%88%86%E7%B1%BB%E4%BB%BB%E5%8A%A1%E4%B8%AD.md
Readme https://github.com/flyskywen/NLP_ability#readme-ov-file
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