« Machine learning » : différence entre les versions
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== Termes privilégiés == | == Termes privilégiés == | ||
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apprentissage | <h3>apprentissage machine</h3> | ||
apprentissage | <h3>apprentissage automatique</h3> | ||
apprentissage statistique | <h3>apprentissage artificiel </h3> | ||
<h3>apprentissage statistique </h3> | |||
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== Anglais == | == Anglais == |
Version du 14 mars 2018 à 14:21
Domaine
Définition
Termes privilégiés
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apprentissage machine
apprentissage automatique
apprentissage artificiel
apprentissage statistique
<poll>
Anglais
Machine learning
Machine learning is a field of computer science that gives computer systems the ability to "learn" (i.e. progressively improve performance on a specific task) with data, without being explicitly programmed.[1]
The name Machine learning was coined in 1959 by Arthur Samuel.[2] Evolved from the study of pattern recognition and computational learning theory in artificial intelligence,[3] machine learning explores the study and construction of algorithms that can learn from and make predictions on data[4] – such algorithms overcome following strictly static program instructions by making data-driven predictions or decisions,[5]:2 through building a model from sample inputs. Machine learning is employed in a range of computing tasks where designing and programming explicit algorithms with good performance is difficult or infeasible; example applications include email filtering, detection of network intruders or malicious insiders working towards a data breach,[6] optical character recognition (OCR),[7] learning to rank, and computer vision.
Contributeurs: Jacques Barolet, wiki