AWS-churn-prediction

Customer churn is a significant problem for businesses as it leads to a reduction in revenue and profitability. Machine learning algorithms are useful in predicting which customers are likely to leave, allowing companies to take proactive measures to reduce churn rates. In this project, three algorithms were employed to develop a highly accurate classifier for churn prediction: logistic regression, decision tree, and random forest. The goal is to identify early warning signs of customer churn and predict which customers are more likely to discontinue the use of the company's products or services.
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project dependencies

all project steps done in aws sagemaker studio with datascience notebook instance no extra libraries need to be installed

report --> has full report about the project
all source file exists in src files used in training
- decision_tree.py
- logistic_regression.py
- random_forest.py