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This project aims to predict the final grades (G2 and G3) of students based on various factors such as age, study time, family support, and more.It utilizes machine learning techniques to make predictions and offers insights into the factors affecting students' grades.
Developed an Internal Mark Calculator website tailored for SRMIST to simplify internal marks calculation. This user-friendly tool allows students to input marks for cycle tests and lab practical and instantly calculate their total internal marks. **Empowers students with a grade predictor to strategize their preparation effectively**.
Working on a simple linear regression model for predicting students' exam scores. Using a dataset with features like study time, family size, and parental backgrounds. This work is for personal training and educational purposes.