Course Code
nlp
Duration
21 hours (usually 3 days including breaks)
Requirements
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.
Overview
이 과정은 영어로 된 텍스트에서 의미를 추출하는 데 관심이있는 사람들을 대상으로 합니다만 다른 언어에도이 지식을 적용 할 수 있습니다.
이 과정에서는 블로그 게시물, 트윗 등 인간이 작성한 텍스트를 사용하는 방법을 다룹니다.
예를 들어 분석가는 광범위한 데이터 소스를 기반으로 결론에 자동으로 도달하는 알고리즘을 설정할 수 있습니다.
Machine Translated
Course Outline
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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