One of the main questions I hear in Artificial Intelligence (AI) classes is about what it is and when to use supervised and unsupervised machine learning techniques.
Today these questions are asked by non-programmers or beginners, because the amount of information on what supervised learning is and how to implement really has to be accessible to those who know or who know and have experience.
These terms imply that they are different models.
Making a metaphor, imagine students being supervised by a teacher who passes a specific goal or target and shows several examples so that they can have a direction on how to learn to perform their task to better reach the target. In the unsupervised, the teacher gives examples, but does not indicate the target to be reached. Students are free to draw their conclusions from the examples.
These techniques address different problem solving.
Which one to use will depend on the business objective.
TARGET : BUSINESS OBJECTIVE
