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阅读排除法技巧整理
GRE阅读答题需把握的原则一览
GRE阅读语法之定语从句
备考GRE阅读需要把握什么时机
GRE阅读常考哪些题型句式
GRE阅读笔记技巧分析
GRE阅读考试题思路分析
GRE阅读理解的三种题型透彻分析
GRE阅读文章特点解析
归纳GRE阅读6种常见长难句结构
锻炼逻辑思维有助于提升GRE阅读能力
GRE阅读题型的举例分析
GRE阅读速度问题如何解决
GRE阅读理解技巧解析
分析GRE阅读的反面信息题
如何攻克GRE阅读难关
GRE阅读考试四大应对方法
GRE阅读主体结构有哪些
GRE阅读命题有哪些规律可循
GRE阅读中不会的词怎么猜
如何对GRE阅读进行针对性训练
GRE阅读辅导五步走
GRE阅读插入语分析
GRE阅读理解如何准确选择答案
如何解决GRE阅读速度慢
GRE良好阅读习惯如何养成
哪些渠道有助于拿到GRE阅读高分
GRE阅读类比类题目分析
从词汇入手备战GRE阅读
GRE阅读中哪三类词汇常备遗忘
| 不限 |
| 英语教案 |
| 英语课件 |
| 英语试题 |
| 不限 |
| 不限 |
| 上册 |
| 下册 |
| 不限 |