In this project, we tried to predict the prices of other houses according to the values of these features with the model we obtained by training a data set containing some features and prices of real houses with linear regression and decision tree regression methods. FOR MORE INFO LOOK TO THE POWERPOİNT SLIDE.
Feature engineering is the process of transforming raw data into a format that boosts the performance of machine learning models. Imagine you're building a model to predict the price of houses. Raw data like street address, number of bedrooms, and square footage might not be enough. Feature engineering helps you extract and create new features that are more relevant and informative for your model.