| DC Field | Value | Language |
|---|
| dc.contributor.author | Bregid, R. D. | - |
| dc.contributor.author | Anisckovets, A. R. | - |
| dc.coverage.spatial | Минск | en_US |
| dc.date.accessioned | 2025-06-02T08:50:21Z | - |
| dc.date.available | 2025-06-02T08:50:21Z | - |
| dc.date.issued | 2025 | - |
| dc.identifier.citation | Bregid, R. D. Artificial intelligence learning methods / R. D. Bregid, А. R. Anisckovets // Электронные системы и технологии : сборник материалов 61-й научной конференции аспирантов, магистрантов и студентов БГУИР, Минск, 21–25 апреля 2025 г. / Белорусский государственный университет информатики и радиоэлектроники ; редкол.: Д. В. Лихаческий [и др.]. – Минск, 2025. – С. 992–993. | en_US |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/59910 | - |
| dc.description.abstract | The report focuses on artificial intelligence (AI) learning, focusing on three main
categories: Supervised Learning, Unsupervised Learning and Reinforcement Learning. The
differences, pros and cons of these methods, as well as the situations in which they are used, are
described. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | БГУИР | en_US |
| dc.subject | материалы конференций | en_US |
| dc.subject | artificial intelligence | en_US |
| dc.subject | Supervised Learning | en_US |
| dc.subject | Unsupervised Learning | en_US |
| dc.title | Artificial intelligence learning methods | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | Электронные системы и технологии : материалы 61-й конференции аспирантов, магистрантов и студентов (2025)
|
