When to use Linear Regression and When to use Logistic regression - use cases Linear Regression is used to find the relation between dependent variable and independent variable.

Logistic Regression is used when dependent variable is categorical.

But this doesn't exactly suffice, what use cases you can use either of these, or can we use a combination of them?
Logistic Regression is used when you know that the data is lineraly seperable/classifiable and the outcome is Binary or Dichotomous but it can extended when the dependent has more than 2 categories.

Linear Regression is used to find the relation and based on the relation between them you can predict the outcome, the dependent variable should be numeric.

What kind of usecases are you expecting? give an example so that we can extend it further.