Supervised Learning

In this kind of learning, we assume that the training examples are labeled.

There are two kinds of Supervised Learning problems:

• Classification

• Regression

Classification

It refers to the task of assigning a label to a given example i.e. to categorize it into one of multiply categories. Ex. spam/not spam, family car/not family car

Here, the output is discrete.

Regression

It refers to the task of predicting a real-valued output. Ex. prediction house value, temperature

Here, the output is continuous.