01 / The brief
The question
Build a regression model that estimates housing prices and supports real estate pricing analysis.
This GitHub project focuses on predicting housing prices using machine learning. It is relevant for the portfolio because it shows regression modeling skills for a real estate pricing problem.
Results & observations
- Created a housing price prediction workflow that estimates property prices from structured data.
- The project demonstrates regression, feature engineering, and model evaluation skills.
Challenges
- Preparing mixed property features
- Handling price prediction errors
- Choosing useful regression metrics
- Turning model output into business insight
Approach
- Prepared housing price data for machine learning.
- Processed numerical and categorical features.
- Trained regression models.
- Evaluated prediction performance and model quality.
Implementation details
Data Preparation
Prepared housing data for regression modeling.
Feature Engineering
Processed property features for model training.
Model Training
Trained regression models to predict house prices.
Model Evaluation
Evaluated prediction quality using regression metrics.
Business Interpretation
Connected predicted prices to real estate decision-making.
Explore the report
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