Probabilistic Machine Learning Approaches for Adaptive User Systems in Developing Economies
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| Format: | Recurso digital |
| Sprache: | Englisch |
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2026
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| _version_ | 1866901591604330496 |
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| author | KAJASICHE, LAWRENCE |
| author_facet | KAJASICHE, LAWRENCE |
| contents | <p class="MsoNormal"><span>Adaptive user systems are becoming increasingly important in modern digital environments because they improve personalization and user interaction. This paper explores probabilistic machine learning approaches for adaptive systems in developing economies. The study focuses on Bayesian-inspired learning systems capable of adjusting applications according to user behavior, educational background, and technological literacy levels. The paper further discusses the relevance of adaptive systems within African digital transformation initiatives.</span></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20284697 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Probabilistic Machine Learning Approaches for Adaptive User Systems in Developing Economies KAJASICHE, LAWRENCE Keywords: adaptive systems, Bayesian learning, machine learning, user modeling, developing economies <p class="MsoNormal"><span>Adaptive user systems are becoming increasingly important in modern digital environments because they improve personalization and user interaction. This paper explores probabilistic machine learning approaches for adaptive systems in developing economies. The study focuses on Bayesian-inspired learning systems capable of adjusting applications according to user behavior, educational background, and technological literacy levels. The paper further discusses the relevance of adaptive systems within African digital transformation initiatives.</span></p> |
| title | Probabilistic Machine Learning Approaches for Adaptive User Systems in Developing Economies |
| topic | Keywords: adaptive systems, Bayesian learning, machine learning, user modeling, developing economies |
| url | https://doi.org/10.5281/zenodo.20284697 |