Using the Ensemble Approach, Predict Students' Achievement

Pupils are the future of a country since they immediately contribute to its development and prosperity via the information they acquire. The kids should be given all the advantages and adequate care they merit for their development and development in order to correctly mould them, which will also mould their classmates since it will inspire them to do better and subsequently lead to better development. To forecast student performances and identify at-risk pupils as as possible so that the proper steps to improve their performance may be taken, computer software and deep neural networks may be utilized. Many additional methods have also been used to measure the effectiveness of the different algorithms. The primary goal of the study is to develop a unique dataset, forecast academic achievement, and then assess that prediction's accuracy using several tree-based group methodologies.