HomeScope: Predictive Real Estate Analytics

• Tech Stack: Python, Pandas, scikit-learn, Matplotlib, Seaborn
• Github URL: Project Link

Built an advanced predictive model to estimate house prices using various regression algorithms. The project involved extensive data cleaning, feature engineering, and visualization to ensure high model performance and accuracy.

Implemented multiple regression models to find the best fit, compared their performance using key metrics, and provided insights into the strengths of each model. This hands-on approach improved understanding of predictive algorithms and model evaluation.

Conducted exploratory data analysis (EDA) to identify trends and relationships in housing features, enhancing the interpretability and reliability of predictions.

This project demonstrates practical data science skills in building and evaluating regression models for real estate price estimation, highlighting the use of industry-standard tools for comprehensive analysis.