You can see this notebook and all my work in th following link on Kaggle ![https://www.kaggle.com/code/dimitriskatos/usa-price-house]
In this notebook we try to predict the price of the houses in different cities of U.S.A.
- At the beginning we clean the data
- We dive into the dataset and finding hidden patterns and inshights by doing E.D.A. We make many visualization to understand the features.
- We apply Feature engineering and the we apply Multiple Linear Regression to determine which of this feature are signigicant for the model.
- The we try some machine learning algorithms such as Regularization Regresion, Decission Trees, Random Forest regressor and Gradient Boosting Regressor.