课程编码
nlp
课程时长
21 小时 通常来说是3天，包括中间休息。
要求
No background in NLP is required.
Required: Familiarity with any programming language (Java, Python, PHP, VBA, etc...).
Expected: Reasonable maths skills (A-level standard), especially in probability, statistics and calculus.
Beneficial: Familiarity with regular expressions.
课程概览
本课程专为有兴趣从书面英语文本中提取意义的人设计，尽管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撰写的文本，如博客文章，推文等...
例如，分析师可以设置一种算法，该算法将根据广泛的数据源自动得出结论。
Machine Translated
课程大纲
Short Introduction to NLP methods
- word and sentence tokenization
- text classification
- sentiment analysis
- spelling correction
- information extraction
- parsing
- meaning extraction
- question answering
Overview of NLP theory
- probability
- statistics
- machine learning
- n-gram language modeling
- naive bayes
- maxent classifiers
- sequence models (Hidden Markov Models)
- probabilistic dependency
- constituent parsing
- vector-space models of meaning
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