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Creating training and test sets

Before you create any model, it is important to split your dataset into two: a training set which will be used to build your churn model, and a test set which will be used to validate your model. To do this, you can use the train_test_split() function from sklearn.model_selection.

You'll practice creating training and test sets in this exercise. The telco DataFrame is available in your workspace.

This exercise is part of the course

Marketing Analytics: Predicting Customer Churn in Python

View Course

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import train_test_split
Edit and Run Code