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. The goal is to develop a predictive model that can assist in understanding the factors that influence student performance.
- numpy
- pandas
- sklearn
- seaborn
- matplotlib
This project demonstrates the application of machine learning in predicting student grades based on various factors. The trained model can be used to make predictions and identify students who may need additional support.
Feel free to contribute, provide feedback, or report issues related to this project.