Telecom Churn Case Study
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Updated
Jan 24, 2021 - Jupyter Notebook
Telecom Churn Case Study
To reduce customer churn, telecom companies need to predict which customers are at high risk of churn.
To predict if a customer will churn, given the ~170 columns containing customer behavior, usage patterns, payment patterns, and other features that might be relevant. Your target variable is "churn_probability"
Predict churn and derive actionable strategies to retain users in a highly competitive telecom environment.
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