Abstract
Machine learning addresses the question of how to build computers that improve automatically through experience. It is one of today’s most rapidly growing technical fields, lying at the intersection of computer science and statistics, and at the core of artificial intelligence and data science. Recent progress in machine learning has been driven both by the development of new learning algorithms and theory and by the ongoing explosion in the availability of online data and low-cost computation. The adoption of data-intensive machine-learning methods can be found throughout science, technology and commerce, leading to more evidence-based decision-making across many walks of life, including health care, manufacturing, education, financial modeling, policing, and marketing.
Keywords
Intersection (aeronautics)Computer scienceArtificial intelligenceCore (optical fiber)Data scienceMachine learningBig dataComputationLyingEngineeringData mining
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Publication Info
- Year
- 2015
- Type
- review
- Volume
- 349
- Issue
- 6245
- Pages
- 255-260
- Citations
- 8710
- Access
- Closed
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Cite This
Michael I. Jordan,
Tom M. Mitchell
(2015).
Machine learning: Trends, perspectives, and prospects.
Science
, 349
(6245)
, 255-260.
https://doi.org/10.1126/science.aaa8415
Identifiers
- DOI
- 10.1126/science.aaa8415