• Semon Raj .A
• Dr.H.Faheem Ahmed

Now a day’s e-learning is smartly growing technology. This technology is more helpful for students to communicate with their professors through chats or emails. ELearning also removes the obstacle of physical presence of an Elearner. The main aim of this paper is to predict student performance in their final exams using different machine learning techniques. Information like attendance, marks, assignments, class participation, seminar, CA, projects and semester are collected to predict student performance. This prediction helps the instructors to analyze their students based on their performance. For that we have used WEKA tool for the prediction of the student performance. WEKA (Waikato Environment for Knowledge Analysis) is one of the data mining too which is used for the classification and clustering using data mining algorithms. This prediction helps the students and the staffs to know how much effort their students need to be put in their final exams to get good marks.

E-learning, Data Mining, Machine Learning algorithms, Data Pre-processing

"Learning Prediction Using Machine Learning Techniques for Students", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 9, page no.23-31, September 2019, Available :http://www.jetir.org/papers/JETIRDD06006.pdf

"Learning Prediction Using Machine Learning Techniques for Students", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 9, page no. pp23-31, September 2019, Available at : http://www.jetir.org/papers/JETIRDD06006.pdf