Natural language processing (NLP) enables computers to understand and manipulate human language by converting unstructured text into structured forms for analysis. It supports text mining across social media, websites, emails, company documents, and academic publications. section 5.1
A practical NLP workflow can:
- Break text into phrases and sentences, identify parts of speech, and extract entities and relationships. section 5.1
- Prepare structured language data for machine-learning tasks such as sentiment analysis and topic modeling. section 5.1
- Process small inputs quickly with generative AI, then switch to dedicated NLP libraries when scale, accuracy, or control matters more. section 5.7
Customer insight from language
A business can analyze customer reviews, social-media posts, or service interactions to track sentiment, identify topics, extract negative feedback, and summarize findings for decisions. section 6.0 section 5.1
Generative AI can translate inputs and outputs, suggest code, and handle small NLP tasks without programming. Treat its answers as hypotheses: inspect generated code, question hidden assumptions, validate outputs against raw records, and divide complex analyses into smaller steps. section 5.7
