Supervised learning is a type of machine learning algorithm that uses a known dataset (labeled data) to predict outcomes. Supervised learning algorithms are trained using labeled data, which is data that has been labeled with the correct answer. For example, a supervised learning algorithm could be used to recognize objects in images by being trained on a dataset of labeled images.

Unsupervised learning is a type of machine learning algorithm that works on unlabeled data. Unsupervised learning algorithms are used to find patterns and relationships in data without being given any labels or outcomes. For example, an unsupervised learning algorithm could be used to cluster data points into groups based on their similarities.

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