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.

Classify Computer Science grades for University of Greenwich

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**.

Scalable and modifiable multimodal classification. Targeting mainly grade-prediction, based on various life-style choices of students.

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.

SmartGrade AI is a predictive academic analysis system using machine learning and databases to monitor and improve student performance.

A machine learning project to predict student final grades using academic and demographic data. Built with pandas, scikit-learn, and visualized with seaborn and matplotlib to gain insights and support early intervention for students.

Excel simulation bulletins ISEN

An ML-based model which predicts the grade of a student at IIT Guwahati.

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