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An Investigation on Educational Data Mining to Analyze and Predict the Student’s Academic Performance Using Visualization

  • J. Dheeraj Kumar
  • K. R. Shankar
  • R. A. K. Saravanaguru
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 862)

Abstract

Presently, educational institutions compile and store huge volumes of data such as student’s enrollment details, academic history, attendance records, and as well as their examination results. Traditional data mining approaches cannot be directly applied for visualization so we are using Pandas software library framework for preprocessing of the academic’s data and visualization of the data using matplotlib and seaborn libraries are used in this approach to get better results and easily understand and predict the outcomes from the data.

Keywords

EDM Academic performance MatplotLib Visualization 

Notes

Acknowledgements

We undertake that we have the required permission to use images/dataset in our work from suitable authority and we shall be solely responsible if any conflicts arise in the future.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • J. Dheeraj Kumar
    • 1
  • K. R. Shankar
    • 1
  • R. A. K. Saravanaguru
    • 1
  1. 1.School of Computer Science & EngineeringVellore Institute of TechnologyVelloreIndia

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