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https://github.com/dod-o/nlp-practice-program
力求囊括主流NLP模型练手项目，不断更新中
https://github.com/dod-o/nlp-practice-program
Last synced: 1 day ago
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力求囊括主流NLP模型练手项目，不断更新中
- Host: GitHub
- URL: https://github.com/dod-o/nlp-practice-program
- Owner: Dod-o
- Created: 2019-02-01T15:35:22.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2020-06-11T16:40:13.000Z (over 4 years ago)
- Last Synced: 2024-12-25T20:07:54.501Z (9 days ago)
- Language: Python
- Homepage:
- Size: 150 MB
- Stars: 277
- Watchers: 9
- Forks: 66
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# NLP练手项目路线
## 写在前面：
很抱歉，这个repo我没有精力再往下写了，看到star竟然还在缓慢地增加，每天在愧疚中度过，甚至以泪洗面。
各位大佬有自己写完的demo，欢迎pull给我！！！我会合并进来，并且署名是你。
工具不限，可以tensorflow，也可以pytorch。可以原创，也可以搬运（不能侵权），希望注释详细，和我现有的代码一样。
我们来做一个nlp最全demo合集吧！冲鸭！
——来自一个面对star惶惶不可终日的nlp搬砖实习生
## 简介
各种NLP练手项目，贯彻注释比代码多的风格，学起来更带劲。[博客地址](http://www.pkudodo.com/)
## 版本：
```TensorFlow 1.4.0```
## 包含内容
### 1.word2vec词嵌入
**词嵌入**：基于skip-gram训练词嵌入矩阵，每个词由300维向量表示，相同意义的词向量相似。
在NLP处理中通常会采用词嵌入来表示每个词。
[-->项目入口](https://github.com/Dod-o/NLP-practice-program/tree/master/1.skip_gram)
[-->代码详解_视频入口](https://www.bilibili.com/video/av42442500)
##### 运行结果 （选取其中一个单词为例，根据词嵌入矩阵计算邻近词）
>**训练前**：
hemoglobin --> alden, vive, deviations, dlp, taj, beauvoir, pillow, allying
有道翻译结果：血红蛋白 --> 奥尔登，vive，偏差，dlp，泰姬陵，波伏娃，枕头，结盟
**训练后**：
hemoglobin --> ligand, molecules, ligands, photosynthesis, aerobic, enzyme, pancreatic, chlorophyll
有道翻译结果：血红蛋白 --> 配体、分子、配体、光合作用、需氧、酶、胰腺、叶绿素
### 2.文本生成
**风格仿写**：学习哈利波特1-7全文，训练结束后给定起始单词（下方运行结果中，给定的起始单词为'Hi, '）,由模型自主生成哈利波特风格的句子。
[-->项目入口](https://github.com/Dod-o/NLP-practice-program/tree/master/2.harry_potter_lstm)
[-->代码详解_视频入口](https://www.bilibili.com/video/av42442500/?p=3)
##### 运行结果
>Hi, he was nearly off at Harry to say the time that and she had been back to his staircase of the too the Hermione?
### 3.字母排序
seq2seq最基础应用，给定单词如bca，使用seq2seq排序为abc。
[-->项目入口](https://github.com/Dod-o/NLP-practice-program/tree/master/3.seq2seq_alphabetical%20order)
##### 运行结果
>the input is: hello
the output is: ['e', 'h', 'l', 'l', 'o']
### 4.摘要生成
seq2seq应用，给定一段话，自动生成摘要。
[-->项目入口](https://github.com/Dod-o/NLP-practice-program/tree/master/4-seq2seq_summary_burner)
##### 运行结果
>------------the text is:----------------
Use olive oil to cook this, salt it well, and it is the best, most tender popcorn I have ever eaten. I add a tiny bit of butter to mine, but don't need it. My nine year old daughter didn't like popcorn until she reluctantly tried this. After a few bites, she consumed half the bowl!
I bought mine at a specialty popcorn shop in Long Grove IL, so I didn't have to pay shipping costs, but when it's gone, I might have to bite the bullet and order it from here.",Spoiled me for other popcorn
------------the summary is:-------------
best tasting popcorn ever