Key Features:

Data Exploration and Preprocessing: Includes data loading, cleaning, feature engineering, and exploratory data analysis (EDA).

XGBoost Model Training: Trains an XGBoost regression model on the Boston Housing Dataset.

Hyperparameter Tuning: Implements techniques like grid search or random search to optimize model hyperparameters for better performance.

Model Evaluation: Evaluates model performance using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), R-squared, and Mean Absolute Error (MAE).