Machine learning is a scientific discipline that is concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases. A learner can take advantage of examples to capture characteristics of interest of their unknown underlying probability distribution. Data can be seen as examples that illustrate relations between observed variables. A major focus of machine learning research is to automatically learn to recognize complex patterns and make intelligent decisions based on data; the difficulty lies in the fact that the set of all possible behaviors given all possible inputs is too large to be covered by the set of observed examples . Hence the learner must generalize from the given examples, so as to be able to produce a useful output in new cases. Artificial intelligence is a closely related field, as are probability theory and statistics, data mining, pattern recognition, adaptive control, computational neuroscience and theoretical computer science.
GRE作文官方题库:历史类
论GRE写作提纲的重要性
GRE写作替换词总结
GRE写作素材:名人名言
实例讲解对付GRE Argument 的思路和破题方法
写GRE Issue 没思路怎么办?
GRE写作:Issue范文赏析之论成功
GRE Issue写作提纲分析
为GRE作文考试加分的句子和词汇
gre写作中aw三个阶段的备考攻略
GRE写作:练习才是硬道理
GRE备考:Issue思路讲解- 法律的弹性
ETS对GRE写作Issue部分的指导
GRE issue 内容分类:art
Issue写作特点及备考建议介绍
零基础学GRE:怎样理解Issue?
GRE写作之Argument提分句式
GRE写作:句子的扩充
GRE写作六类素材整理
GRE写作范文——拯救濒危物种
GRE写作:Issue范文之实践论
GRE issue 内容分类: science
托福写作如何“改写”名人名言
GRE写作:高分表达能力很重要
新GRE Issue分类归纳
非常实用的GRE作文结尾模板整理
GRE写作:十大论证方法
GRE Argument写作常用论证句式整理
GRE写作范文怎么用
如何培养GRE作文考试逻辑思维
| 不限 |
| 英语教案 |
| 英语课件 |
| 英语试题 |
| 不限 |
| 不限 |
| 上册 |
| 下册 |
| 不限 |