Solving Real-World Problems Using Machine Learning with Big Data

Abstract

Machine learning algorithms use big data to identify future trends and make predictions for your business. In an industry where understanding consumer patterns can lead to big improvements, machine learning is very efficient at deciphering data. Deploying machine learning can be a giant leap forward for an enterprise, and it's more than just integrating it at the top tier. This requires a redefinition of workflows, architecture, data collection and storage, analytics and other modules. The scope of the system overhaul should be assessed and clearly communicated to the appropriate parties. A major focus of machine learning is the development of computer programs that can access data and use it to learn. The learning process begins with observations or data to find patterns in the data and make better decisions. The main goal of data analysis using machine learning is for computers to automatically learn and adjust their behavior accordingly, without the need for human intervention or interaction. Considering the many applications where data analysis is found in the real world, this article will therefore focus on big data analysis and explore the fundamental applications of machine learning as one of the tools of artificial intelligence. The purpose of this article is to understand the aspects, components, applications, and challenges of introducing machine learning into the real world.