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
Introduction to NLP Methods
- Word and sentence tokenization
- Text classification
- Sentiment analysis
- Spelling correction
- Information extraction
- Parsing
- M 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 prior background in NLP is required.
Prerequisite: Familiarity with at least one programming language (e.g., Java, Python, PHP, VBA).
Expectation: Solid mathematical proficiency (equivalent to A-level standards), particularly in probability, statistics, and calculus.
Advantageous: Familiarity with regular expressions.
21 Hours
