Customer Churn Prediction Model

• Developed a machine learning model to predict customer churn.

• Preprocessed data using encoding, normalization, and feature selection techniques.

• Addressed class imbalance to improve model performance.

• Evaluated the model using Precision, Recall, F1-Score, and Confusion Matrix.

• Achieved a strong classification score and improved churn prediction accuracy.

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