Machine learning techniques, essentially employ statistics to identify patterns in massive amounts of data including words, numbers, images, and other forms of data, carry out all of those tasks. To address specific problems, a machine-learning program can employ data that can be digitally saved. The data analysis employed a multiple regressions model to identify the key variables that affect whether delighted both students and teachers are with e-learning. E-learning has emerged as a result of the widespread adoption of the internet, various information and communication technologies, and distant learning. Machine learning (ML), which is transforming learning, has a significant influence on learners, knowledge, and studies. Educators are employing ML to recognize challenging students proactively and take the necessary steps to boost retention and accomplishment. To make fresh findings and get additional insight, academics are expediting their research with ML. Machine learning (ML) techniques are now frequently utilized to assist in solving practical issues based on statistical information. E-learning methodologies are a cutting-edge approach to education and learning in the digital world.

Machine learning, E-learning, Education strategy, Digital transformation, Accountability, prospective teacher educators, Higher education, Technology Enhanced Learning Environments.