This Jupyter Notebook showcases using data science and machine learning techniques to create and train a linear regression model for predicting students' math scores. The dataset used was a Students' Performance dataset consisting of 1000 records and 8 features(categorical and numerical), it was obtained from Kagle under the title "Student Performance Dataset".
- Data preprocessing: Handling missing values, scalling, and encoding.
- Linear regression model: Creation, training, and evaluation.
- Model performance evaluation: Comparison of mean squared error, mean absolute error, and R-squared values.