Supervised learning is typically done in the context of classification, when we want to map input to output labels, or regression, when we want to map input to a continuous output.

What is supervised learning used for?

Supervised learning, also known as supervised machine learning, is a subcategory of machine learning and artificial intelligence. It is defined by its use of labeled datasets to train algorithms that to classify data or predict outcomes accurately.

Where we can use supervised learning?

Supervised learning can be used for those cases where we know the input as well as corresponding outputs. Unsupervised learning can be used for those cases where we have only input data and no corresponding output data. Supervised learning model produces an accurate result.