METHODOLOGY OF MACHINE LEARNING IN STATISTICAL ANALYSIS

Mirziyodova, Gulnoza

Рақамли иқтисодиёт ва ахборот технологиялари · 2025-yil

Annotatsiya

Machine learning (ML) has become a revolutionary approach in statistical analysis with improved data interpretation and predictive modeling abilities. In this study, the methodological underpinnings of ML in statistical applications are explored, with approaches like supervised and unsupervised learning, reinforcement learning, and deep learning being highlighted. Through a review of important algorithms, performance metrics, and real-life applications, this study offers interesting perspectives on how ML augments conventional statistical methods. The findings highlight the growing synergy between ML and statistical analysis in favor of advances in data-driven decision-making

Maqola ma’lumotlari
MualliflarMirziyodova, Gulnoza
JurnalРақамли иқтисодиёт ва ахборот технологиялари
Nashr sanasi2025-03-31
Jild5
Son1
Betlar273-278
TilIngliz

Kalit so‘zlar

machine learning, statistical analysis, supervised learning, unsupervised learning, predictive modeling

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