Abstract: In the current scenario, this is difficult to predict students’ future results based on his/her current performance. As the outcome of this, the teacher can advise him/her to overcome the poor result, and also it can coach the student. By finding out the dependencies for final examinations. The system suggests to students about subject/course selection for the upcoming semester and act as roles of adviser/teacher. Due to improper advice and monitoring a lot of student’s futures in dark. This is difficult for a teacher to analyze and monitors the performance of each and every student. The system can give feedback to teachers about how to improve student performance. This paper carried out a literature review from the year 2003 to 2021. The system predicts his/her future results by applying Machine Learning Algorithms like k-Nearest Neighbor (k-NN), Support Vector Machine (SVM), and Naive Bayes at an earlier stage.

Keywords: SVM , Dataset, ML, Training Module.

| DOI: 10.17148/IARJSET.2022.9477