MACHINE LEARNING ALGORITHMS FOR PREDICTIVE ANALYTICS IN BIG DATA

Abstract

The rapid growth of big data has revolutionized decision-making processes across various sectors by providing vast amounts of information for analysis. Predictive analytics, powered by machine learning (ML) algorithms, enables organizations to forecast future outcomes based on historical data, enhancing operational efficiency and strategic planning. This article explores the role of machine learning algorithms in big data predictive analytics, examining their applications, challenges, and advancements. We highlight key algorithms such as linear regression, decision trees, random forests, and neural networks, and discuss their effectiveness in handling complex and large-scale data sets. Additionally, we address challenges such as data quality, interpretability, and computational costs. The article also provides real-world examples of how these algorithms have been applied in sectors such as healthcare, finance, and e-commerce to predict trends and inform decision-making.