Student Marks Prediction Using Linear Regresion

Authors

  • Shivani Babar TY Student, Department of Computer Engineering, Sahakar Maharshi Shankarrao Mohite Patil Institute of Technology and Research, Akluj, Solapur, Maharashtra Author
  • Varad Mane TY Student, Department of Computer Engineering, Sahakar Maharshi Shankarrao Mohite Patil Institute of Technology and Research, Akluj, Solapur, Maharashtra Author
  • Ms. Jadhav S. P. Lecturer, Department of Computer Engineering, Sahakar Maharshi Shankarrao Mohite Patil Institute of Technology and Research, Akluj, Solapur, Maharashtra Author

DOI:

https://doi.org/10.29070/2s1xp761

Keywords:

Classification Prediction, Machine Learning, Data Cleaning, Data Processing, Linear Regression

Abstract

This study examines how machine learning applications affect teaching and learning in higher education, as well as how to improve the learning environment. Students' interest in online and digital courses grew significantly, and websites like Course Era, Udemy, and others became increasingly important. We use innovative machine learning applications in teaching and learning while taking into account the students' background, previous academic performance, and other factors. Because of the enormous class numbers, it would be impossible to support each individual student in each open learning course, which could raise the dropout rate at the conclusion. In this study, we use linear regression, a machine learning algorithm, to predict outcomes.

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References

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Published

2022-03-01