Machine Learning Modeling for Predictive Analysis

In this project, I built and compared multiple machine learning models to predict target values based on structured data. The process included data cleaning, preprocessing, feature encoding, and scaling to prepare the dataset. I trained and evaluated models such as Linear Regression, Random Forest, and XGBoost, using cross-validation and hyperparameter tuning to improve performance. The evaluation was based on metrics like Mean Absolute Error, Mean Squared Error, and R² score.