One of the most important tasks in machine learning is building a linear regression model (you can find more information in the Linear Regression with Python course).

Since we use a linear function in this model, we can use the correlation between features and target to indicate how significant a particular feature is for this model.

We will use the 'Heart Disease Dataset' now: it contains 14 features, including the predicted attribute, which refers to the presence of heart disease in the patient. Your task is to calculate attribute importance using correlation:

1. Calculate correlations between features and target.
2. Print these correlations in ascending order.