Higher education institutions are often very curious to know about the success rate of the students throughout their study. For this reason, they need to use several methods like physical examination, Statistical methods and currently prevailing data mining techniques for the prediction of student\'s performance. An upcoming area of research which uses techniques of data mining is known as Educational Data Mining. It involves machine learning algorithms and statistical techniques to help the user for interpretation of student\'s learning habits, their academic performance and further improvement if required. In this paper we will discuss various techniques of data mining which are useful for predicting performance level of students. For this we used dataset of kalboard 360 and applied it on weka to analyze the data mining techniques.
Software And Hardware
• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL