Machine learning and deep learning algorithms work well where future estimations and predictions are required. Notably, in educational institutions, machine learning, and deep learning algorithms can help instructors predict learners' learning performance. Furthermore, the prediction of learners' learning performance can assist instructors and intelligent learning systems in taking preemptive measures/early engagement/early intervention measures so that the learning performance of weak learners could be in creased, thus reducing learners' failures/dropout rates. In this study, we propose an intelligent learning system that provides adaptive feed back and support to learners.