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Machine Learning

What are features and labels?

Features are inputs used by a model.

✳ Beginner◷ 3 short lessons · learn at your paceTEXT-BASED LEARNING
Before you dive in: outcomes & prerequisites

No AI experience required. Start with the simple explanation.

A beginner learning path: understand the idea, follow an everyday example and check your understanding. Read the three lessons in order.

Start here · beginner

01 · Understand the idea

In simple words

Features are inputs used by a model. A label or target is the desired output for a training example in supervised learning. Choose features that would actually be available when making a prediction. Information recorded after the outcome can create a misleadingly good model.

Words to know

Feature: input information. Label: the desired category or value for an example.

Pause here and explain the definition in one sentence without copying it. The aim is to describe what the system does, not to memorise an impressive phrase.

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