Evolutionary machine learning builds smart education big data platform: Data-driven higher education

Abstract

The development of machine learning has promoted the construction of smart education platforms. It is of great significance to deeply investigate the usage of machine learning techniques in smart education. In this paper, we explore how to utilize evolutionary algorithms and machine learning algorithms to build a smart education big data platform to promote the intelligent development of higher education and better assist the establishment of the smart education system. We combine evolutionary algorithms and machine learning models to build a personalized course recommendation model for the smart education big data platform, which uses deep belief networks and swarm intelligence evolutionary algorithms to recommend relevant content based on the interests of learners. We take advantage of the feature extraction of deep belief networks and combine supervised learning and unsupervised learning to design an intelligent recommendation model for teaching content. At the same time, we utilize the advantages of evolutionary algorithms to tune the model parameters to obtain the best parametric model. We compare our method with other methods on public dataset to show the model performance.