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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
This repository presents a comprehensive exploration of customer churn using various machine learning algorithms, including linear regression, logistic regression, decision tree, and random forest. Through this project, we aim to understand and predict customer churn, providing valuable insights for proactive customer retention strategies.