Advanced Predictive Modeling & Regression Analysis Pipeline

This project implements an end-to-end Machine Learning pipeline tailored for a comprehensive regression task using the House Prices dataset. The workflow is structured into organized, modular stages designed to handle real-world data challenge remediations and extract precise predictions.

Key processes include rigorous data preprocessing, feature engineering (addressing missing values and outliers), feature selection driven by correlation analysis, and the implementation/evaluation of multiple robust regression algorithms.