Machine learning with big data to solve real-world problems

Abstract

Machine learning algorithms use big data to learn future trends and predict them for businesses. Machine learning can be very efficient for deciphering data in industries where understanding consumer patterns can lead to big improvements. The use of machine learning can be a giant leap for businesses and cannot simply be integrated as the top layer. This requires redefining workflow, architecture, data collection and storage, analytics, and other modules. The magnitude of the system overhaul should be assessed and clearly communicated to the appropriate stakeholders. The main focus of machine learning is to develop computer programs that can access data and use it to learn. The learning process starts with observations or data, to find a pattern in the data and make better decisions. The main goal of data analysis using machine learning is that it allows the computer to learn automatically without human intervention and help and can adjust its actions accordingly. Considering the many applications that data analysis has found in the real world, therefore, in this article, a review of the basic applications of machine learning as one of the tools of artificial intelligence has been done with an emphasis on big data analysis. The purpose of this article is to understand the dimensions, components and applications, and challenges of using machine learning in the real world.