Laptop Price Prediction

This project develops a model to predict laptop prices based on various features. Utilizing a detailed preprocessing approach, the model handles both categorical and continuous variables through encoding and feature engineering. The dataset includes features such as RAM, weight, CPU clock speed, and more. A Random Forest Regressor is employed for the prediction task, with performance evaluated using metrics like Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R-squared.