This project contains real estate price prediction with linear regression models. I have used the common linear regression models (Ridge, Lasso, ElasticNet), Random Forest, Gradient Descent and XGBoost models to solve the problem.
The dataset comes from Kaggle and can be find here.
- Real estate price prediction with linear regression models - Real_estate_regression.ipynb
- Python script with price predictions models - prices_model.py
The project is created with:
- Python 3.6
- libraries: pandas, numpy, sklearn, seaborn, matplotlib.
Running the project:
To run this project use Jupyter Notebook or Google Colab.