Abstract

In the modern digital world, where data flows like a never-ending river, machine learning (ML) stands as the sentinel, understanding patterns, anticipating trends, and increasing decision-making across a myriad of different disciplines. The revolutionary potential of machine learning has touched practically every aspect of our lives, ranging from the tailored suggestions that keep us interested in streaming platforms to the complicated algorithms that help physicians diagnose illnesses at earlier, more curable stages. These applications are just a few examples of how ML has had an impact on our lives. The purpose of this article is to provide a complete assessment of the methods and approaches that may be used to manage data privacy and security in machine learning initiatives

Description