Analyzing and prediction of academic performance of the students using an existing database.
Machine learning based data mining techniques are used to accelerate process of student performance prediction using Linear Regression technique. Here we have used a dataset of 25 entries of their study hours and the previous scores. With the advancement of machine learning supervised and unsupervised techniques developing these kinds of applications are helping teachers to analyze students in better way compare to existing methods. So we have taken some steps to perform this action as follows i)Fetched the dataset. ii)Trained and tested the dataset. iii)Plotted the entries in a graph where x-axis contains study Hours and y-axis contains Marks Percentage. iv) Imported the Linear Regression library and fitted the data. v) Predicted the result and compared with the dataset result.