Coding Challenge: Unsupervised Learning

Practice using unsupervised learning algorithms on preprocessed data.

We'll cover the following

We’ll now work with a dataset containing information on a bank’s customer base, containing the following variables:

  • customerID: The customer’s unique ID.

  • gender: The customer’s gender.

  • SeniorCitizen: The customer’s senior citizen status.

  • Partner: The customer’s relationship status.

  • Dependents: The customer’s number of dependents.

  • tenure: The length of time (in months) that the individual has been a customer.

  • Services that the customer has subscribed to:

    • PhoneService

    • MultipleLines

    • InternetService

    • OnlineSecurity

    • OnlineBackup

    • DeviceProtection

    • TechSupport

    • StreamingTV

    • StreamingMovies

  • Contract: The customer’s current contract type: “Month-to-Month,” “One Year,” “Two Year.”

  • PaperlessBilling: The customer’s preference regarding paperless billing.

  • PaymentMethod: The customer’s preferred method of bank payment: bank withdrawal, credit card, mailed check.

  • MonthlyCharges: The customer’s current total monthly charge.

  • TotalCharges: The customer’s total charges.

  • Churn: Whether or not the customer has exited or churned (our target variable).

Here is an example of how it looks:

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