Сучасні підходи використання нейронних мереж в аналізі текстів

dc.contributor.advisorГлибовець, Андрійuk_UA
dc.contributor.authorДраговоз, Даміанuk_UA
dc.date.accessioned2025-09-09T13:41:30Z
dc.date.available2025-09-09T13:41:30Z
dc.date.issued2025
dc.description.abstractIn recent years, artificial intelligence (AI) has experienced a significant rise in popularity and usage. One of the breakthroughs responsible for this surge was the invention of GPT language models, which captivated public attention. This work aims to explore fundamental concepts in AI that are utilized in such models while focusing more on NLP-specific tasks. While more advanced topics—such as the entire architecture of transformer networks and other cutting-edge techniques—are not examined in exhaustive detail, the material presented here is sufficient to provide a robust conceptual foundation. The objective is not to cover every aspect exhaustively but to ensure a clear understanding of why these models are effective, how the various components integrate, and what makes NLP systems so successful.en_US
dc.identifier.urihttps://ekmair.ukma.edu.ua/handle/123456789/36541
dc.language.isoen_USen_US
dc.statusfirst publisheden_US
dc.subjectintelligence (AI)en_US
dc.subjectGPT language modelsen_US
dc.subjectNLPen_US
dc.subjectterm paperen_US
dc.titleСучасні підходи використання нейронних мереж в аналізі текстівuk_UA
dc.typeOtheren_US
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