Machine Learning (ML)
Also known as: ML, Statistical Learning
In one sentence
A branch of artificial intelligence where computers learn patterns from data and improve at tasks through experience, rather than following explicitly programmed rules.
Explain like I'm 12
Instead of telling a computer every single rule, you show it thousands of examples and it figures out the patterns on its own—like learning to recognise dogs by looking at lots of dog photos instead of memorising a checklist of features.
In context
Machine learning powers many tools you use daily without realising it. Netflix recommendations learn what you enjoy by analysing your viewing history alongside millions of other users. Email spam filters learn to identify junk mail from patterns in billions of flagged messages. Voice assistants like Siri improve their speech recognition by processing countless audio samples. The three main approaches are supervised learning (training with labelled examples), unsupervised learning (finding hidden patterns in unlabelled data), and reinforcement learning (learning through trial and error with rewards).
See also
Related Guides
Learn more about Machine Learning (ML) in these guides:
Machine Learning Fundamentals: How Machines Learn from Data
BeginnerUnderstand the basics of machine learning. From training to inference—a practical introduction to how ML systems work without deep math or coding.
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