不需要 NLP 背景。
要求：熟悉任何程式设计语言（Java、Python、PHP、VBA 等）。
预期成绩：合理的数学技能（A-level 标准），尤其是在概率、统计和微积分方面。
有益的：熟悉正则表达式。
本课程专为有兴趣从书面英语文本中提取含义的人而设计，尽管这些知识也可以应用于其他人类语言。
该课程将介绍如何使用人类编写的文本，例如 博客文章、推文等......
例如，分析师可以设置一种演算法，该演算法将根据广泛的数据源自动得出结论。
NLP 方法简介
- 单词和句子分词
- 文本分类
- 情感分析
- 拼写更正
- 资讯提取
- 解析
- 含义提取
- 问答
NLP 理论概述
- 概率
- 统计学
- 机器学习
- N-gram 语言建模
- 朴素贝叶斯
- Maxent 分类器
- 序列模型 （Hidden Markov Models）
- 概率依赖性
- 成分解析
- 向量空间意义模型
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