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Predictive modelling techniques to mitigate customer churn within the telecommunications industry. Utilizing a dataset of over 7,000 customers, we evaluate various predictive models including Logistic Regression, Decision Trees, Naïve Bayes, and Neural Networks to identify key factors influencing customer churn

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kp27302/Telecom-Churn---ML

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Predictive modelling techniques to mitigate customer churn within the telecommunications industry. Utilizing a dataset of over 7,000 customers, we evaluate various predictive models including Logistic Regression, Decision Trees, Naïve Bayes, and Neural Networks to identify key factors influencing customer churn

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