Difference between revisions of "Machine Learning (ML)"
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Machine learning (ML) is a field devoted to understanding and building methods that let machines "learn" – that is, methods that leverage data to improve computer performance on some set of tasks. It is seen as a broad subfield of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. - [https://en.wikipedia.org/wiki/Machine_learning#History_and_relationships_to_other_fields Machine learning | Wikipedia] | Machine learning (ML) is a field devoted to understanding and building methods that let machines "learn" – that is, methods that leverage data to improve computer performance on some set of tasks. It is seen as a broad subfield of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. - [https://en.wikipedia.org/wiki/Machine_learning#History_and_relationships_to_other_fields Machine learning | Wikipedia] | ||
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Revision as of 17:40, 28 April 2023
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Machine learning (ML) is a field devoted to understanding and building methods that let machines "learn" – that is, methods that leverage data to improve computer performance on some set of tasks. It is seen as a broad subfield of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. - Machine learning | Wikipedia
