MACHINE LEARNING: KEY PRINCIPLES AND APPLICATIONS
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How to Cite

Turg’unovich , O. A. . . (2025). MACHINE LEARNING: KEY PRINCIPLES AND APPLICATIONS . Confrencea, 4(4), 104–107. Retrieved from https://confrencea.org/index.php/confrenceas/article/view/1633

Abstract

Machine Learning (ML) is a pivotal subset of Artificial Intelligence (AI) that
empowers systems to learn from data and make informed decisions without
explicit programming. This paper delves into the foundational principles of ML,
including supervised, unsupervised, and reinforcement learning, and explores their
diverse applications across various sectors such as healthcare, finance, retail,
manufacturing, and transportation. By examining real-world implementations and
case studies, the paper underscores the transformative impact of ML on modern
industries. Additionally, it addresses challenges like data privacy, model
interpretability, and ethical considerations, offering insights into the future
trajectory of ML technologies.

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Copyright (c) 2025 Olimov Asqarali Turg'unovich