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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Issue: August 2022

Volume 7 | Issue 8

Impact factor: 8.15

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Paper Title: Student Performance Analysis using Machine Learning
Authors Name: Chippa Sowmya , Vasara Divya , Puppala Preshitha , Bhukya Prasanna Kumari , Sri Swathi
Unique Id: IJSDR2204029
Published In: Volume 7 Issue 4, April-2022
Abstract: Analyzing and predicting academic performance is essential for any educational institution. Predicting student performance can help teachers take action to create a strategy to improve performance early. With the development of machine learning supervised methods and supervised methods that develop these types of applications help teachers better analyze students compared to existing methods. In this case student mark prediction using back-to-back project efficiency is a hypothetical guess as previous students mark and predict marks in the next lesson and calculate model accuracy. Educational institutions are using new technologies to improve the quality of education but most of the applications used in colleges are related to services and development rather than web applications that help students to do online training and exams. There are many ways teachers can learn more about student performance. In view of this problem machine learning methods are used to predict students' marks based on past marks and to predict the outcome. Lower descent models are used to predict student performance and predict marks in the next lesson
Cite Article: "Student Performance Analysis using Machine Learning", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 4, page no.165 - 168, April-2022, Available :http://www.ijsdr.org/papers/IJSDR2204029.pdf
Downloads: 000101745
Publication Details: Published Paper ID: IJSDR2204029
Registration ID:200213
Published In: Volume 7 Issue 4, April-2022
DOI (Digital Object Identifier):
Page No: 165 - 168
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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