Machine learning: Trends, perspectives, and prospects

被引:5419
作者
Jordan, M. I. [1 ]
Mitchell, T. M. [2 ]
机构
[1] Univ Calif Berkeley, Dept Elect Engn & Comp Sci, Dept Stat, Berkeley, CA 94720 USA
[2] Carnegie Mellon Univ, Machine Learning Dept, Pittsburgh, PA 15213 USA
关键词
NEURAL-NETWORKS;
D O I
10.1126/science.aaa8415
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页码:255 / 260
页数:6
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