In supervised machine learning, problems are categorised between "Classification" and "Regression".
In a regression problem, we are trying to predict results within a continuous output.
Example:
If we have an inventory of similar products, we want to know how many of them we can sell in the next 3 months.
In a classification problem, we are trying to predict results by mapping variables into categories.
Example:
Trying to classify if a new fruit is a banana or an apple based on the color and shape of the fruit.
(a) Regression - Given a picture of a person, we have to predict their age on the basis of the given picture
(b) Classification - Given a patient with a tumor, we have to predict whether the tumor is malignant or benign.