
- 233 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
About this book
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Key Features
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Book Description
????????????????????????????, ??????????????????????????????????????????????????????????, ????????????????????, ????????????????????????????????Python????????????(?Gensim?spaCy?)?????????????????????????, ????????????????????????????????????????15?, ????????????????Python??????????spaCy?????Gensim????????????NER?????????????????????????????????????????????????????????????????Keras?spaCy????????????????????????????????????????????, ???????????????, ???????????????????Python?????????????????????, ????????????????????????????????????Python???????????????????????, ?????????????
What you will learn
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- ?????????Gensim?????
- ????Keras???????
Who this book is for
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Information
Table of contents
- 版权信息
- 版权
- 版权声明
- 内容提要
- 关于作者
- 关于审稿人
- 前言
- 资源与支持
- 第1章 什么是文本分析
- 第2章 Python文本分析技巧
- 第3章 spaCy语言模型
- 第4章 Gensim:文本向量化、向量变换和n-grams的工具
- 第5章 词性标注及其应用
- 第6章 NER标注及其应用
- 第7章 依存分析
- 第8章 主题模型
- 第9章 高级主题建模
- 第10章 文本聚类和文本分类
- 第11章 查询词相似度计算和文本摘要
- 第12章 Word2Vec、Doc2Vec和Gensim
- 第13章 使用深度学习处理文本
- 第14章 使用Keras和spaCy进行深度学习
- 第15章 情感分析与聊天机器人
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