Natural Language Processing
Understand language models, text processing, language understanding and the NLP tasks behind everyday product features.
This series covers the language tasks behind search, support routing, analytics and document processing: what each does and how it is evaluated.
It complements LLM Basics. References include the standard NLP textbook and key papers.
What You’ll Learn
Natural language processing covers classification, information extraction, summarisation, translation, question answering and semantic search. Modern systems often use one pre-trained model adapted to many tasks, choosing model size to match accuracy, cost and latency needs.
NLP turns human language into something software can act on, and back again.
BERT showed that one pre-trained model, fine-tuned per task, could set new results across many language benchmarks.