IMPACT OF THE MACHINE LEARNING FEATURE ON THE DEVELOPMENT OF TECHNOLOGY

ABSTRACT

A total of six billion people reside in developing nations. Researchers in subjects ranging from sociology to statistics, ecology to economics have long been interested in the specific issues that these places confront. With the rapid maturation of machine learning (ML) approaches, academics are increasingly turning to machine learning to enhance development research and practice. To provide an example, supervised machine learning methods may be used to offer expert decision assistance for health care in resource-limited areas, while deep learning techniques can be used to analyze satellite data to develop fresh economic indicators. Nonetheless, there are significant obstacles to deploying machine learning in the underdeveloped world. Data availability, processing capability, and Internet connectivity in developing nations are often much less developed than in developed ones. The convergence of machine learning’s enormous promise with the actual constraints faced by developing world environments has sparked a growing corpus of study in machine learning for developing world environments (ML4D). In this essay, we will take a look at this increasing body of literature. For the purpose of determining the scope of the study, we provide a formal definition for ML4D and conduct a survey of significant application issues in the field. For the design and implementation of ML4D initiatives that promote important development goals, we provide best practices derived from the literature. Throughout this essay, we will concentrate on research that heavily depends on machine learning. Since a result, we will refrain from discussing themes that are exclusively related to Big Data or information technology, as they have already been well covered in prior publications. These characteristics are applicable to both the issues which are being discussed and the remedies which are being suggested to those challenges. It takes into consideration five principles of growth: "social, economic, health, environmental, and institutional development", to name a few.

FULL TEXT