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

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.

  21 Hours
 

Number of participants


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Dates are subject to availability and take place between 9:30 am and 4:30 pm.
Open Training Courses require 5+ participants.

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