So, the task which we want to accomplish will be a supervised learning task as it has a label(median_house_value), which we need to predict, provided other features.
So as it belongs to supervised learning, we can further classify it as whether our task is a classification or a regression task.
Classification- In a classification task, we need to classify our data points in classes based on several parameters. So, when our label contains discrete values (where every value represents a class), then we consider our task as a classification task.
For example,, classifying whether an email is spam or not, classifying whether a fruit is an apple, mango, or a banana, rating a movie from 1 to 5, all these are examples of classification as their output value will be discrete.
Regression- In a regression task, we need to approximate the output value for a data point based on several parameters. So, when our label contains continuous values, then we consider our task as a regression task.
For example, Predicting the future stock price of a company, Predicting how temperature affects ice-cream sales, all these are examples of regression as their output value will be continuous.
For example, a classification task to classify apples and bananas and a regression task to predict stock prices will look like-
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