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Predict Student Success with ML Tool by saanum012005 is a document available to read on EtoBox.

What is Predict Student Success with ML Tool about?

The project aims to predict student performance based on study hours and attendance using a logistic regression model. An interactive web app built with Streamlit allows users to input data and receive predictions on whether a student will pass or fail. The project highlights the potential of machine learning in identifying students who may need academic support.

Author

saanum012005

Language

EN