Machine Learning BasicsLesson 2
Lesson 29 min
Supervised Learning
Learning from labelled examples — classification vs regression.
What you will learn
- ✓What labelled data is
- ✓Classification vs regression
- ✓Common algorithms for each
Explanation
Supervised learning uses data where each example has a known answer (label). The model learns to map inputs to those answers.
There are two kinds. Classification predicts a category — spam/not-spam, cat/dog, fraud/legit. Regression predicts a number — house price, temperature, sales.
A quick test: if the answer is a label, it is classification; if it is a quantity, it is regression.
Real-world use
Predicting whether a transaction is fraud is classification; predicting how much a customer will spend next month is regression.
Common mistakes
- • Using a regression model when the target is actually a category (or vice versa).
Practice
List five prediction tasks and label each as classification or regression.
Knowledge check
0/2 answered1. Predicting next month's revenue (a number) is...
2. Supervised learning requires...
Answer all questions to check.