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Qu'est-ce (qui) est machine learning - définition
Machine learning
![An artificial neural network is an interconnected group of nodes, akin to the vast network of [[neuron]]s in a [[brain]]. Here, each circular node represents an [[artificial neuron]] and an arrow represents a connection from the output of one artificial neuron to the input of another.](https://commons.wikimedia.org/wiki/Special:FilePath/Colored neural network.svg?width=200 "An artificial neural network is an interconnected group of nodes, akin to the vast network of [[neuron]]s in a [[brain]]. Here, each circular node represents an [[artificial neuron]] and an arrow represents a connection from the output of one artificial neuron to the input of another.")
![A decision tree showing survival probability of passengers on the [[Titanic]]](https://commons.wikimedia.org/wiki/Special:FilePath/Decision Tree.jpg?width=200 "A decision tree showing survival probability of passengers on the [[Titanic]]")
![linear boundary]]. Here, the linear boundary divides the black circles from the white.](https://commons.wikimedia.org/wiki/Special:FilePath/Svm max sep hyperplane with margin.png?width=200 "linear boundary]]. Here, the linear boundary divides the black circles from the white.")
SCIENTIFIC STUDY OF ALGORITHMS AND STATISTICAL MODELS THAT COMPUTER SYSTEMS USE TO PERFORM TASKS WITHOUT EXPLICIT INSTRUCTIONS
Statistical learning; Machine Learning; Machine learning algorithm; Learning algorithms; Feature discovery; Strengthening learning algorithms; Computer machine learning; Adaptive machine learning; Learning algorithm; List of open-source machine learning software; List of machine learning software; Learning machine; Machine-learning; Machine-learned; Applications of machine learning; History of machine learning; Automatic learning algorithms; Ethics of machine learning; Genetic algorithms for machine learning; Applied machine learning; Machine learning applied; Applying machine learning; Ethics in machine learning; Ethical issues in machine learning; Self-teaching computer; Self-learning (machine learning); Embedded Machine Learning; Machine learning hardware; AI training; Generalization (machine learning)
Machine learning (ML) is the study of computer algorithms that can improve automatically through experience and by the use of data. It is seen as a part of artificial intelligence.
machine learning
SCIENTIFIC STUDY OF ALGORITHMS AND STATISTICAL MODELS THAT COMPUTER SYSTEMS USE TO PERFORM TASKS WITHOUT EXPLICIT INSTRUCTIONS
Statistical learning; Machine Learning; Machine learning algorithm; Learning algorithms; Feature discovery; Strengthening learning algorithms; Computer machine learning; Adaptive machine learning; Learning algorithm; List of open-source machine learning software; List of machine learning software; Learning machine; Machine-learning; Machine-learned; Applications of machine learning; History of machine learning; Automatic learning algorithms; Ethics of machine learning; Genetic algorithms for machine learning; Applied machine learning; Machine learning applied; Applying machine learning; Ethics in machine learning; Ethical issues in machine learning; Self-teaching computer; Self-learning (machine learning); Embedded Machine Learning; Machine learning hardware; AI training; Generalization (machine learning)
The ability of a machine to improve its performance based on
previous results.
Neural networks are one kind of machine learning.
[More examples? Net resources? Web page? ]
(1995-02-15)
Automated machine learning
PROCESS OF AUTOMATING THE END-TO-END PROCESS OF MACHINE LEARNING
AutoML; Architecture search; Automated feature engineering; Auto ml; No-code machine learning; Low-code machine learning
Automated machine learning (AutoML) is the process of automating the tasks of applying machine learning to real-world problems. AutoML potentially includes every stage from beginning with a raw dataset to building a machine learning model ready for deployment.
Exemples du corpus de texte pour machine learning
1. Research from the lab group will focus on a range of subjects, Microsoft said, including multimedia search, machine learning, distributed computing and data mining.
2. They hoped that Xerox‘s experience in machine learning, linguistics and text categorization would increase the system‘s accuracy on the ‘open microphone‘ task.
3. Though she grew up watching her mother at the sewing machine, learning the craft with each loving stitch of the family‘s clothes, Brown never considered making it a career until two years ago, when she entered Second Life.
4. The system now looks at all the individual words within the sentence, takes into account the system‘s confidence that it has correctly recognized each individual word, and uses a sophisticated machine–learning algorithm to weigh the various pieces of positive and negative information.