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