machine learning - перевод на греческий
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machine learning - перевод на греческий

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)
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  • 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]]
  • linear boundary]]. Here, the linear boundary divides the black circles from the white.

machine learning         
μάθηση μηχανής
μάθηση μηχανής      
machine learning
threshing machine         
  • Threshing of paddy by machine, Bangladesh.
  • Open-air museum in [[Saint-Hubert, Belgium]].
  • Video of a petrol-powered machine threshing rice in [[Hainan]], China
AGRICULTURAL MACHINE
Thrashing machine; Threshing machines; Thrashin' machines; Horse threshing machine; Threshing-machine
αλωνιστική μηχανή

Определение

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)

Википедия

Machine learning

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 algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.

A subset of machine learning is closely related to computational statistics, which focuses on making predictions using computers, but not all machine learning is statistical learning. The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. Data mining is a related field of study, focusing on exploratory data analysis through unsupervised learning.

Some implementations of machine learning use data and neural networks in a way that mimics the working of a biological brain.

In its application across business problems, machine learning is also referred to as predictive analytics.

Примеры употребления для 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.