Prediction of Education Performance using Deep Learning
S.Ganesh Kumar1, G.Harshavardhan Reddy2
1S. Ganesh Kumar, Associate Professor, Department of Computer Science and Engineering, SRM Institute of Science and Technology, kattankulathur Campus, India.
2G. Harshavardhan Reddy, Department of Computer Science and Engineering, SRM Institute of Science and Technology, kattankulathur Campus, India.
Manuscript received on 04 May 2019 | Revised Manuscript received on 09 May 2019 | Manuscript Published on 13 May 2019 | PP: 361-364 | Volume-8 Issue-7S May 2019 | Retrieval Number: G10640587S19/19©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Among all the sectors educational sector plays major role which is used to increase training by observing understudies execution and endeavoring to comprehend the understudies’ learning. By collecting marks from the students toward the finish of the semester, at any point they have the issue of not profiting the understudies that have officially taken the course. To get advantage for the present students an input ought to be given progressively and tended to continuously. This would empower understudies and instructors to address educating and learning issues in the most valuable manner for the understudies. Dissecting understudies’ execution utilizing information mining strategies can distinguish the understudies’ sure or negative actualities, or significantly progressively refined exhibitions, that understudies have towards the present educating. In this paper this we examine a student’s performance act by considering profound learning procedure calculations CNN.
Keywords: Student Performance Prediction, Deep Learning for Education, Neural Networks.
Scope of the Article: Computer Science and Its Applications