Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Brief 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
- Maximum entropy classifiers
- Sequence models (Hidden Markov Models)
- Probabilistic dependencies
- Constituent parsing
- Vector-space models of meaning
Requirements
No prior background in NLP is necessary.
Required: Proficiency in at least one programming language (e.g., Java, Python, PHP, VBA).
Expected: Solid mathematical foundation (at the A-level standard), with particular emphasis on probability, statistics, and calculus.
Beneficial: Understanding of regular expressions.
21 Hours
