Big Data, Artificial Intelligence, and Machine Learning Support for E-Learning Frameworks

Abstract

Today's e-rendering frameworks are essential in various fields such as computer graphics, virtual reality, and augmented reality to provide an effective and impressive education to modern society. The integration of big data, artificial intelligence (AI), and machine learning (ML) techniques into e-rendering frameworks hold significant potential for enhancing rendering efficiency, optimizing resource allocation, and improving the quality of rendered outputs. With the advent of big data, massive amounts of rendering-related data can be collected and analyzed. This data includes rendering parameters, scene descriptions, user preferences, and performance metrics. By applying data analytics, important information can be derived, allowing for more informed decision-making in rendering processes. Additionally, AI techniques, such as neural networks and deep learning, can be employed to learn from the collected data and generate more accurate rendering models and algorithms.