This review paper consists of literature survey to prediction of scholarship by using Machine Learning and Data Mining technique. Along with this it contains a small description of ML/DM which are used by the researchers. It also describes data sets as very important in ML/DM methods. Machine Learning becomes most popular in the field of IT industry. Nowadays Machine Learning and Data Mining turn as a powerful technique which applicable for various fields such as IT, Education sector and also in business sector too. The different types of ML/DM algorithms are addressed by using all this technique. The algorithms which give more accuracy results in detection of continuity of every student's scholarship such as NAive Bayes, Decision Tree and k-NN. Finally, the proposed model will provide a list of candidates, who deserve to have a scholarship and also discussion has been made on accuracy of each techniques which was used to get a result.
Software And Hardware