This repository contains a machine learning project aimed at predicting house prices using a dataset from the Kaggle House Prices: Advanced Regression Techniques competition. The goal is to predict the sales price for each house based on various features using a Random Forest model, with model performance evaluated using the Root Mean Square Error (RMSE).

The dataset used in this project can be found on Kaggle: House Prices Dataset

A Random Forest regressor is utilized due to its effectiveness in handling large datasets with multiple features that may have complex relationships and interactions. After trying over 25 data prepration techniques, I was able to reduce the RMSE score by 44%._