Machine learning


Ontology type: npg:Subject  | skos:Concept     


Concept Info

NAME

Machine learning

DESCRIPTION

Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have multiple applications, for example, in the improvement of data mining algorithms.

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curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/ontologies/subjects/machine-learning'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/ontologies/subjects/machine-learning'

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curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/ontologies/subjects/machine-learning'


 

This table displays all metadata directly associated to this object as RDF triples.

91 TRIPLES      9 PREDICATES      21 URIs      15 LITERALS

Subject Predicate Object
1 sg:ontologies/subjects/machine-learning sgo:license sg:explorer/license/
2 sgo:sdDataset onto_subjects
3 rdf:type npg:Subject
4 skos:Concept
5 rdfs:label Machine learning
6 skos:altLabel AI (Artificial Intelligence)
7 AIs (Artificial Intelligence)
8 Artificial Intelligence
9 Computer Reasoning
10 Computer Vision System
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12 Knowledge Acquisition (Computer)
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14 Knowledge Representation (Computer)
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17 skos:broader sg:ontologies/subjects/computational-biology-and-bioinformatics
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19 skos:inScheme sg:ontologies/subjects/
20 skos:prefLabel Machine learning
21 sg:ontologies/subjects/ dcterms:description The Nature Subjects Taxonomy is a polyhierarchical categorization of scholarly subject areas which are used for the indexing of content by Springer Nature.
22 dcterms:title Nature Subjects Taxonomy
23 sgo:sdDataset onto_subjects
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