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What is Machine Learning Systems?

They are computer systems that learn on their own by analyzing data and can make more accurate predictions over time.

Overview

These systems self-learn rules by extracting examples from data rather than being explicitly programmed. Once trained, it uses past experiences to make predictions when faced with new, never-seen data. They improve their performance over time with a constant flow of data.

Analogy: It's like a child touching fire once, learning it, and never touching it again, without having to tell you repeatedly that fire burns.

How it works

Large data sets are given to the model, the model finds patterns in this data and creates a mathematical model to produce a result.

Where it is used

It is used in recommendation systems, fraud detection, health analysis and autonomous vehicles.

Frequently asked questions

How is it different from artificial intelligence?

Machine learning is a sub-branch of artificial intelligence focused on learning from data; Not every artificial intelligence uses machine learning.

Related terms

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This explanation was written in plain language for TreScout and machine-translated from the Turkish original · the Turkish version prevails. If something looks wrong or missing, write to hello@trescout.com. Read in Turkish →