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AI glossary

Supervised Learning

Supervised learning is a machine learning method where a model learns from examples that are already labeled with the correct answer.

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In this guide

  1. 1What Supervised Learning means
  2. 2Why Supervised Learning matters

What Supervised Learning means

In supervised learning, each training example comes with the right answer attached, like a worked exercise. The model studies many of these pairs and learns to connect the input to the correct output.

For example, to build a model that detects spam, you provide emails each labeled "spam" or "not spam." The labels act like a teacher's marking, guiding the model so it can later judge new, unlabeled emails on its own.

Why Supervised Learning matters

Supervised learning is one of the most common ways AI models are trained, so the term appears often. Knowing it helps you understand how many AI tools were built.

It is behind many everyday AI tools, from spam filters to forecasts
It explains why labeled, high-quality data is so valuable
Knowing it helps you understand AI articles and discussion
It gives useful context for working with AI tools

Frequently asked questions

Supervised learning uses labeled data with the correct answers provided. Unsupervised learning uses unlabeled data and asks the model to find patterns on its own, with no answer key.

More AI terms

Unsupervised LearningA machine learning method where a model finds patterns in data that has no labels or correct answers.Reinforcement LearningA machine learning method where a model learns by trial and error, guided by rewards for good outcomes.APIA defined way for two software systems to talk to each other and share data or features.Workflow AutomationSetting up a series of tasks to run automatically by connecting your apps and tools together.Retrieval-Augmented GenerationA technique that lets an AI look up relevant information first, then use it to give a more accurate answer.EmbeddingA way of turning text or other data into numbers that capture meaning, so AI can compare similarity.

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