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README.md

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----
-license: cc-by-4.0
----
-Customer churn prediction dataset of a fictional telecommunication company made by IBM Sample Datasets.
-Context
-Predict behavior to retain customers. You can analyze all relevant customer data and develop focused customer retention programs.
-
-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
-
-
-Credits for the dataset and the card:
-- [Kaggle](https://www.kaggle.com/datasets/blastchar/telco-customer-churn)
-- [Latest version of the dataset by IBM Samples team](https://community.ibm.com/community/user/businessanalytics/blogs/steven-macko/2019/07/11/telco-customer-churn-1113)

scikit-learn--churn-prediction/csv-train.parquet

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