How Machines Learn
📋 What it is
Machine learning is how AI improves at a task by finding patterns in lots of examples (data), instead of being told every rule.
🗣️ Coach says
Instead of a human writing every rule, machine learning shows the computer thousands of EXAMPLES and lets it find the pattern. Show it 10,000 cat photos labelled “cat” and it learns what a cat looks like — from data, not rules.
🧠 Memory hook
AI learns from EXAMPLES (data), not from being told every rule.
😂 Giggle
What do you call a robot that always takes the long way around?
A path-o-logical thinker!
😲 Whoa!
To learn to recognise a cat, an AI might study MILLIONS of labelled photos — far more than any human sees in a lifetime, which is why it needs so much data.
✅ Quick check: How does an AI learn to tell cats from dogs?
Say your answer out loud first — then reveal.
By studying many labelled EXAMPLES (photos tagged cat/dog) and finding the patterns that separate them — learning from data.
Machine learning generalises a pattern from many examples.
🧪 Try it! (2 minutes)
Think how YOU learned what a dog is — from seeing many dogs, not a rulebook. AI learns the same way.