This project focuses on predicting forest fire areas using the Fire Weather Index (FWI) dataset. Key methods include the use of Log Transform to normalize the burned area data, improving the performance of linear regression models. Data analysis and visualizations like histograms and QQ plots are utilized to explore patterns and model accuracy.

Function Transformer is part of feature engineering it converts probability density function to normal distribution