Supervised learning is the most common and studied type of learning because it is easier to train a machine to learn with labeled data than with un-labeled data. Depending on what you want to predict, supervised learning can used to solve two types of problems: regression or classification.
Regression Problem: If you want to predict continuous values, such as trying to predict how many hours will a patient stay at this hospital, you would use regression. This type of problem doesn’t have a specific value constraint because that could be any number of days, hours, or minutes.
Classification Problem: If you’re interested in a problem like: “Am I ugly?”then this is a classification problem because you’re trying to classify the answer into two specific categories: yes or no (in this case the answer is yes to the question above).