admin管理员组文章数量:1130349
前言:
本人所考学校往年的英文文献翻译主要涉及:数据挖掘,人工智能,深度学习,5G网络,SQL定义,编译器
本人在半吊子练习过程中,把我读的一些些比较好用来练习的文献摘要和相关知识(仅提供英文)做了汇总。(持续更新到复试前,做一名合格的半吊子,恩!)
如果你想突击(当然这是不切实际的),这篇博文谨献给给那些和我一样不知道怎么准备这玩意又想找个心里安慰的考研党们一个心灵的依靠;
如果你想踏踏实实练习,就必须至少提前一个月每天上外刊读英文文献哦!
如果你是英文大佬,就看个好玩吧o( *  ̄︶ ̄ * )o
Anyway,如果对你有用就可以点个赞哦,xiexie~
冲刺阶段必背的英语问答题(附加艾宾浩斯记忆表)考研复试_英语面试_必备的30个问题
专题目录
- 数据挖掘(Data Mining)
- 人工智能(Artificial Intelligence)
- 深度学习(Deep Learning)
- 5G网络(5G)
- SQL定义
- 编译器(Compiler)
数据挖掘(Data Mining)
NO.1:
In the current era of big data, the mining and analysis of massive data is particularly important. Data mining technology has been widely applied in the fields of media, finance, medical care, transportation and e-commerce.However, the complexity and diversity of big data and the particularity of the application of data mining technology in various industries have also put forward new theoretical and technical challenges in the field of data mining.
NO.2:
The era of big data for the data mining technology has brought more opportunities and problems, such as the big data content for more efficient data mining algorithm and the accumulation of large data more quickness requirement of real-time data mining algorithms, the complexity of the large data diversity requires more flexible data mining algorithm, the universality of big data in all walks of lif
前言:
本人所考学校往年的英文文献翻译主要涉及:数据挖掘,人工智能,深度学习,5G网络,SQL定义,编译器
本人在半吊子练习过程中,把我读的一些些比较好用来练习的文献摘要和相关知识(仅提供英文)做了汇总。(持续更新到复试前,做一名合格的半吊子,恩!)
如果你想突击(当然这是不切实际的),这篇博文谨献给给那些和我一样不知道怎么准备这玩意又想找个心里安慰的考研党们一个心灵的依靠;
如果你想踏踏实实练习,就必须至少提前一个月每天上外刊读英文文献哦!
如果你是英文大佬,就看个好玩吧o( *  ̄︶ ̄ * )o
Anyway,如果对你有用就可以点个赞哦,xiexie~
冲刺阶段必背的英语问答题(附加艾宾浩斯记忆表)考研复试_英语面试_必备的30个问题
专题目录
- 数据挖掘(Data Mining)
- 人工智能(Artificial Intelligence)
- 深度学习(Deep Learning)
- 5G网络(5G)
- SQL定义
- 编译器(Compiler)
数据挖掘(Data Mining)
NO.1:
In the current era of big data, the mining and analysis of massive data is particularly important. Data mining technology has been widely applied in the fields of media, finance, medical care, transportation and e-commerce.However, the complexity and diversity of big data and the particularity of the application of data mining technology in various industries have also put forward new theoretical and technical challenges in the field of data mining.
NO.2:
The era of big data for the data mining technology has brought more opportunities and problems, such as the big data content for more efficient data mining algorithm and the accumulation of large data more quickness requirement of real-time data mining algorithms, the complexity of the large data diversity requires more flexible data mining algorithm, the universality of big data in all walks of lif
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