Diamond Price Prediction Using Linear Regression

This project implements a machine learning regression model to predict diamond prices based on carat weight. The dataset is preprocessed by handling missing values and encoding categorical features. A Linear Regression model is trained using scikit-learn and evaluated with standard regression metrics including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R² score. The project also includes data visualization to analyze the distribution of carat weight and price, as well as a scatter plot to show the relationship between them. Users can provide a carat weight as input, and the trained model predicts the corresponding diamond price.