Applications of Machine Learning Algorithms in Data Mining for Big Data Analytics

Abstract

This paper explores the integration of machine learning algorithms in data mining for big data analytics, focusing on the role of supervised, unsupervised, and deep learning techniques. It provides an overview of the foundational aspects of data mining in the context of big data and examines various machine learning algorithms that enhance data processing and analysis. Practical applications in key sectors such as healthcare, finance, marketing, and smart cities are discussed, showcasing how machine learning drives innovation and improves decision-making. The paper also addresses challenges like scalability, data privacy, and ethical considerations, and highlights future directions, including algorithm improvements, explainable AI, and edge computing. The conclusion emphasizes the transformative potential of machine learning in advancing big data analytics while ensuring ethical responsibility.