Getting started with supervised machine learning
Supervised learning is a type of machine learning where the algorithm learns from a labeled dataset, which consists of input features and their corresponding target variables or labels. These labels are the “response variable,” “target variable,” or “output variable” – in other words, the thing you are trying to predict.
There are two types of supervised modeling that we will focus on:
- Regression
- Classification
Let’s take a closer look at them.
Regression versus classification
Regression is a specific type of supervised learning where the goal is to predict continuous numerical values. In a regression task, the algorithm learns a mapping between input features and a continuous target variable. The output of the regression model is a continuous value, which can represent quantities such as price, temperature, sales, or any other real-valued quantity. Linear...
