What is Machine Learning? What are its Real-World Applications?

Traditional programming gives computers specific rules - do this, then this, or when this happens, do this. Machine learning doesn’t do that - it lets AI systems learn from experiencing different kinds of data. It’s like if you don’t know what a giraffe is and someone shows you a picture - you don’t need to memorize everything that makes a giraffe a giraffe. You just look at the picture. Machine learning is like that but with a lot more photos!

You don’t tell the computer exactly what to do - you show it lots of examples and let it figure out the patterns. If it knows the pattern it can make predictions about new data - even if it’s never seen it before.

This approach works well for tasks that are hard to program with rules but easy to demonstrate with examples. How do you write rules for recognizing spam email? It's easier to show the system thousands of spam and non-spam emails and let it learn the difference.

The Three Main Types of Machine Learning

Supervised learning is like learning with a teacher. You show the AI examples with the right answers already marked. For instance, you might show it emails labelled as "spam" or "not spam" so it can learn to identify spam in new emails.