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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,
Published in Springer Singapore
2019
Pages: 179 - 188
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.

About the journal
JournalData powered by TypesetAdvances in Intelligent Systems and Computing Information Systems Design and Intelligent Applications
PublisherData powered by TypesetSpringer Singapore
ISSN2194-5357
Open Access0