Telecom Customer Churn Prediction using Tree Methods

A telecom customer churn prediction supervised machine learning project is a project that uses machine learning to identify customers who are at risk of canceling their service based on historical data of customer behavior.

Python - Numpy - Pandas - Matplotlib - Seaborn - Sci-kit Learn

https://www.kaggle.com/datasets/blastchar/telco-customer-churn

About Dataset Context "Predict behavior to retain customers. You can analyze all relevant customer data and develop focused customer retention programs." [IBM Sample Data Sets]

Content Each row represents a customer, each column contains customer’s attributes described on the column Metadata.

The data set includes information about:

Customers who left within the last month – the column is called Churn Services that each customer has signed up for – phone, multiple lines, internet, online security, online backup, device protection, tech support, and streaming TV and movies Customer account information – how long they’ve been a customer, contract, payment method, paperless billing, monthly charges, and total charges Demographic info about customers – gender, age range, and if they have partners and dependents

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