This project understands how the student's performance (test scores) is affected by other variables such as Gender, Ethnicity, Parental level of education, Lunch and Test preparation course. Using various data analysis and visualization techniques I obtained valuable insights that can be used to improve students' performance.
First, the data set is cleaned and prepared for analysis. Then, two regression models are applied; multiple linear regression model and Decision tree model. The two models are then evaluated and compared using metrics like R^2 and Mean Squared Error.