Design of Automatic Education Classification Management System in Cognitive Web Services Platforms Using Machine Learning Techniques

Abstract

Adequate learning resources help students develop their instructional methods, beliefs, attitudes, and general abilities to go beyond a superficial understanding of a subject. It is found that lack of knowledge, inadequate search skills, and lacks of time were all obstacles that hindered library patrons from easily accessing educational resources. It is discovered that patrons of libraries were unable to easily access educational resources because of a lack of knowledge, poor search skills, and a lack of time. Design of automatic education classification management system (D-AECMS) is a proposal in this paper to create and implement cloud-based educational resources and management strategies that support economic development in the classroom. Predictive model-based quality inspection in industrial manufacturing using machine learning techniques and edge cloud computing technology is now possible.