Advanced Prediction of Performance of Student in University Using Machine Learning Techniques

For university, college and school students, predicting academic success is a vital challenge. The area of computer science is machine learning, which lets the computer learn without external programs. In the current project, the dataset is maintained on a cloud server and accessed by means of queries. For computer teaching methods, there are two approaches: one is supervised and the other unattended. K-mean clustering, and ensemble methods such as Random Forest and the XgBoost algorithm, are used in uncontrolled learning. Evaluation of every student organization