Imagine a computer is like a kid learning to ride a bike. At first, it wobbles and falls, that's like making mistakes. But each time it tries again, it gets a little better. A computer learns in the same way: it starts with guesses and keeps improving by using what it learned from its mistakes.
How it works:
- The computer makes a guess about something (like whether an image is a cat or a dog).
- If it's wrong, it adjusts its thinking a little bit.
- It keeps doing this until it gets really good at telling the difference between cats and dogs.
Examples
- A computer learns to tell a cat from a dog by looking at lots of pictures and adjusting its guesses every time it makes a mistake.
- Just like you get better at riding a bike after falling a few times, the computer improves with each incorrect guess.
- Imagine training your pet to sit, you give it treats when it does right, but not if it messes up.
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See also
- How Does a Robot Learn?
- How Does a Robot Actually Learn New Tasks?
- What Is the Difference Between ‘Artificial Intelligence’ and ‘Machine Learning’?
- How Does a Computer Know What You're Thinking?
- How Do Computers Understand Human Speech?
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