Supervised Learning Crash Course

Supervised learning is a fundamental concept in machine learning, where we train models on labeled data to predict outcomes. This article will provide an overview of supervised learning, its types, and some practical examples.

Types of Supervised Learning

1. Regression

Regression is used when the target variable is continuous. The goal is to predict a numerical value.

Example: Predicting house prices based on features like area, number of rooms, etc.

2. Classification

Classification is used when the target variable is categorical. The goal is to predict a class label.

Example: Classifying emails as spam or not spam based on content.

Practical Examples

Image Recognition: Classifying images into categories such as cats, dogs, and cars.
Speech Recognition: Transcribing spoken words into written text.
Medical Diagnosis: Predicting diseases based on patient symptoms and medical records.

Resources

For more information on supervised learning, you can check out our Machine Learning Crash Course.