机器学习:趋势,前景和前景
1Department of Electrical Engineering and Computer Sciences, Department of Statistics, University of California, Berkeley, CA, USA. jordan@cs.berkeley.edu tom.mitchell@cs.cmu.edu.
Science (New York, N.Y.)
|July 18, 2015
概括
机器学习使计算机能够从经验中学习,推动人工智能和数据科学的进步. 它的数据密集型方法正在改变医疗保健和金融等各个领域的决策.
科学领域:
- 计算机科学
- 统计数据
- 人工智能
- 数据科学
背景情况:
- 机器学习专注于通过数据暴露来提高性能的系统.
- 这是一个快速发展的技术领域.
- 进步是由新的算法,理论见解和增加的数据可用性推动的.
研究的目的:
- 提供机器学习的作用和影响的概述.
- 突出最近进步背后的驱动力.
- 为了说明机器学习方法的广泛应用.
主要方法:
- 开发新的学习算法和理论框架.
- 充分利用大量数据的可用性.
- 使用低成本计算能力的进步.
主要成果:
- 在机器学习能力方面取得了重大进展.
- 在不同领域广泛采用数据密集型方法.
- 加强基于证据的决策.
结论:
- 机器学习是计算机科学和统计学交叉的关键领域.
- 它的应用正在彻底改变从医疗到营销的各个行业.
- 该领域的增长与数据和计算资源密切相关.
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