An Improved Computational Solution for Cloud-Enabled E-Learning Platforms Using a Deep Learning Technique

Abstract

The sharable e-learning platform can be presented as a useful learning environment for students on the cloud computing infrastructure. Virtual classrooms are momentarily taking the place of conventional ones, which means that e-learning is becoming more popular. There are currently no strategies for estimating how much cloud resources will be used. Because of this, students can access learning objects without deciding to follow a different learning management system (LMS). The proposed deep learning-based e-learning platform (DL-E-LP) can enable separate LMS embedded in multiple e-learning standards to share the learning objects. Using a smart learning system, teachers can keep track of their students' progress more easily. The convolutional neural network has been used to develop face recognition and monitor students' knowledge learning level in deep learning. The use of modern technologies and smart classrooms makes learning easier for all students. The proposed paradigm is both efficient and productive through experimentation.