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Built a logistic regression based predictive model to identify customers at high risk of churn and identify the main indicators of churn.

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logistic-regression predictive-modeling churn-prediction churn-user-prediction predictive-analytics prediction logistic-regression-algorithm jupyterlab churn-modelling

telecom-churn-prediction-model's Introduction

Telecom-Churn-Prediction-Model

Built a model to predict churn. The predictive model serves two purposes:

It will be used to predict whether a high-value customer will churn or not, in near future (i.e. churn phase). By knowing this, the company can take action steps such as providing special plans, discounts on recharge etc.

It will be used to identify important variables that are strong predictors of churn. These variables may also indicate why customers choose to switch to other networks.

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