Things we do for this Project

•         Using cutting edge data analysis techniques, implement a solid logistic regression model with the aim of forecasting student graduation probability.

•          To improve the interpretability and accuracy of student graduation probability projections, use a Decision Tree model.

•         To ensure transparency and repeatability, perform a thorough study, providing thorough reasons for model selections and documenting important findings.

•          Create an engaging presentation and thorough report while following principles to clearly convey the approaches, findings, and implications of the models created for this project.