|
Balise : Éditeur de wikicode 2017 |
| (24 versions intermédiaires par 2 utilisateurs non affichées) |
| Ligne 1 : |
Ligne 1 : |
| | #REDIRECTION [[ Apprentissage automatique ]] |
|
| |
|
| == Domaine ==
| | [[Catégorie:ENGLISH]] |
| [[Category:Vocabulary]] | |
| [[Category:Apprentissage profond]]
| |
| | |
| == Définition ==
| |
| | |
| | |
|
| |
| | |
| == Termes privilégiés ==
| |
| | |
| <poll />
| |
| Plusieurs termes sont proposés<br />lequel vous semble le plus juste ?
| |
| | |
| apprentissage machine<br />
| |
| | |
| apprentissage automatique<br />
| |
| | |
| apprentissage artificiel <br />
| |
| | |
| 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.
| |
| | |
| <br/>
| |
| <br/>
| |
| <br/>
| |
| <br/>
| |
| <br/>
| |
| <br/>
| |
| <br/>
| |
