Predictions ML Quiz

What you'll be asked

1. In the context of customer insights, what is the primary purpose of a predictive model?
2. When building a model to predict customer churn, which of the following is considered a 'feature' rather than a 'target'?
3. Why is it important to split your dataset into 'training' and 'testing' sets when developing a machine learning model?
4. Which of the following scenarios best describes a 'Propensity Model' in customer insights?
5. You notice your predictive model has high accuracy on the training data but performs very poorly on the validation/test data. What is the most likely cause of this issue?

Answers and explanations come after you submit.