What Is Machine Learning? A Plain-English Guide
Machine learning is software that learns patterns from data to make predictions or decisions, instead of being explicitly programmed with rules.
Quick version: machine learning is software that learns from examples instead of being told every rule.
The core idea
Traditional software follows rules a person wrote. Machine learning flips that: you show the system many examples, and it learns the patterns itself. Feed it past sales and it forecasts future demand; show it labelled images and it learns to recognise objects.
Why data matters
Because ML learns from examples, the quantity and quality of data largely determine the outcome. That's why good data foundations matter so much. ML is a powerful prediction tool — not magic — and turning it into something dependable is the work of applied AI.
Frequently asked questions
What is machine learning in simple terms?
Machine learning is a way of building software that learns patterns from examples in data, then uses those patterns to make predictions or decisions — instead of a developer writing explicit rules for every case.
What is machine learning used for?
Common uses include recommendations, demand forecasting, fraud detection, image recognition and language understanding — anywhere patterns in data can inform a decision.
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