Paper Title
Predictive Analyses: University Dropout Cases

Abstract
During their university studies, students encounter several problems and challenges which hinder their normal courses and which leads to dropping-out. Our article will be dealing with a study of the problem of dropping-out at university. This study includes dynamic programming along with machine learning. We will focus on two main methods which are KNN, which based on the notion of similarity between data and the well-known method SVM, which can crack the problems of classification. We will also derive practical solutions using predictive analytics. And this would include application making predictions with real world example from University of Faculty of Chariaa of Fez. Keywords - dynamic programming, machine learning, SVM, KNN, predictive analytics