# word2vec

## word2vec

* [返回顶层目录](https://github.com/luweikxy/machine-learning-notes/tree/994efe9a1942533ce4f543c98b52dec4b6225352/SUMMARY.md)
* [word2vector概述](/machine-learning-notes/word2vec/word2vec-introduction.md)
* [word2vector算法原理](/machine-learning-notes/word2vec/word2vec-algorithm-principle.md)
* [word2vector代码解析](/machine-learning-notes/word2vec/word2vec-source-code-analysis.md)
* [word2vector实践](https://github.com/luweikxy/machine-learning-notes/tree/994efe9a1942533ce4f543c98b52dec4b6225352/content/natural-language-processing/word2vec/word2vect-practice.md)

## word2vector概述

word2vector概述点击[这里](/machine-learning-notes/word2vec/word2vec-introduction.md)跳转。

## word2vector算法原理

word2vector算法原理点击[这里](/machine-learning-notes/word2vec/word2vec-algorithm-principle.md)跳转。

## word2vector代码解析

word2vector代码解析点击[这里](/machine-learning-notes/word2vec/word2vec-source-code-analysis.md)跳转。

## word2vector实践

word2vector实践点击[这里](/machine-learning-notes/word2vec/word2vec-practice.md)跳转。


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://luweikxy.gitbook.io/machine-learning-notes/word2vec.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.