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.
SAT阅读需切记的两个高分要点
SAT考试的词汇特点与解析
突破SAT阅读生词关有法可循
SAT阅读常见重要词汇整理(1)
SAT阅读模拟题之life stories of Native American
SAT文章阅读步骤和技巧有哪些?
如何突破SAT阅读拿高分?
SAT阅读解题思路指导:理解与推理
SAT阅读文章解题步骤和技巧
美国高考SAT阅读测试的应对策略
SAT阅读解题关键词汇:态度词
SAT阅读备考指导:抓住阅读文章的主干
模拟试题在SAT阅读备考中的作用
5个SAT阅读常见问题应对方法解答
SAT题型指导--Sentence Completion
三个关键点提升SAT阅读分数
SAT阅读六大题型解题技巧
SAT阅读需要克服的三个基础难题
SAT阅读备考方法指导:精读法
SAT阅读考试答题方法指导
克服四个关卡 彻底突破SAT阅读
SAT填空两大逻辑关系:同义重复&反义重复
SAT阅读到底难在哪里?
SAT阅读考试答题技巧与步骤
NEW SAT单词准备完全计划
SAT阅读高分技巧之明喻和暗喻
专家详解SAT阅读考试难点
SAT阅读题型该如何备考
详细分析SAT阅读的突破途径
准确把握SAT填空题的句子结构
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