报告题目：Rough sets and Rosseta in mathematical education
报告人：汤建国
报告时间：2019.11.10 9:00—11:00
报告地点：数学楼307
Rough set, a theory proposed by Pawlak, is a useful tool for processing uncertainty problems and has been used in in many fields such as data mining and machine learning. Rough sets provide an approximation ways to characterize the uncertainty of knowledge, which has been proven to be an effective methods to solve uncertainty problems in reality and attract more and more people to study it. Some researchers have developed a software, named Rosseta, to help people study rough set and solve problems with it. In the software, many common algorithms are embedded in it such as data discretization, rule extraction and reduction, and so on. This report will show two application examples in mathematical education.
报告题目：Python Data Analysis and Application in mathematical education
报告人：汤建国
报告时间：2019.11.10 14:00—17:30
报告地点：数学楼307
With the advent of the era of cloud computing, data analysis technology will help enterprise users to acquire, manage, process and organize massive data in a reasonable time, and provide positive help for enterprise business decision-making. As a cutting-edge technology, data analysis is widely used in the Internet of things, cloud computing, mobile Internet and other strategic emerging industries. Although big data is still in its infancy in China, its business value has emerged, and many enterprises and individuals begin to pay attention to big data analysis technology. As an important big data analysis software, python has been studied and applied by more and more people and enterprises, and has become the most popular data analysis tool. This report will show how to use Python for data analysis through two application examples in mathematical education.
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