Supervised learning is a fundamental concept in machine learning, where an algorithm learns from labeled training data to make predictions or decisions. In this tutorial, we will explore the basics of supervised learning, its different types, and practical examples.

Types of Supervised Learning

  1. Classification

    • This type of supervised learning is used when the output variable is categorical. For example, predicting whether an email is spam or not.
    • Classification Example

  2. Regression

    • Regression is used when the output variable is continuous. For instance, predicting house prices based on various features.
    • Regression Example

Practical Examples

  • Email Spam Filter: Using classification algorithms to determine if an email is spam or not.
  • House Price Prediction: Using regression models to predict the price of a house based on its features.

Further Reading

For more detailed information on supervised learning, you can check out our Machine Learning Basics tutorial.