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How computers recognize patterns and make decisions without being explicitly programmed

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machine learning

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The inputs that a model uses to make decisions

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features

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the output you are trying to decide or predict with a model

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label

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When a human trains a model to learn with examples

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supervised learning

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a computer program designed to make a decision

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model

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Finding patterns in data that doesn't have any labels

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unsupervised learning

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giving examples to a model so it can learn

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training

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data that can be separated into groups

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categorical data

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predicting a category based on other features

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classification

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data that can be counted or measured

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numerical data