Teknosys learning library

Natural language processing: from understanding to generation

Natural language processing (NLP) brings together machine learning and linguistics to work with human language. It covers tasks such as text classification, sentiment analysis, named entity recognition, information extraction, semantic search, translation, summarization, and conversational assistance. Different architectures solve different problems: a model designed to understand a sentence is not necessarily designed to generate an open-ended response.

Try asking the AI chat to compare BERT and GPT, explain the difference between RNN and RNTN, outline an entity-extraction pipeline, or suggest how to evaluate a summarization system. These topics describe the wider NLP ecosystem, not a claim that every architecture is currently hosted by this website.

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