Data Science(什么是数据科学)
科学上网时看到的有关于Data Science的理解,感觉挺好的,就翻一下。
Data science is about understanding systems, whether they be natural systems such as climate, or man-made systems like the economy.
(数据科学可以称之为理解系统,无论这个系统是自然系统,例如天气系统,或者人造的生态环境系统)。
Scientists have been conducting experiments for centuries, but recent advances in technology have enabled us to utilize data to understand systems at a much larger scale.
(科学家已经为这个方向努力了几个世纪,最近在科学技术方面的发展,使得我们能够通过利用大规模的数据来理解系统)
Individual data points represent snapshots of a system's behavior, and as you collect more data on that system, you build up a dataset that you can use to analyze and understand the system as a whole. Some examples of datasets include:
单个的数据点代表了一个系统行为的快照,当你对于这个系统收集的数据越来越多,你就可以创建一个数据集用来分析和理解整个系统。一些数据集的例子如下:
A public company's daily stock prices
上市公司每天的股票价格
GPS location data for Uber rides
对于使用Uber的GPS信息
Familiar software products like Microsoft Excel allow you to explore data, but aren't suitable for data science because they:
与之类似的软件产品Microsoft Excel也使得你能够浏览数据,但是并不适用于数据科学,主要有以下几点问题:
don't scale to larger datasets.
Excel并不能扩展到更大的数据集
don't allow you tweak and run machine learning algorithms.
并不能使你运行相应的机器学习算法
make it challenging to reproduce your work.
重现你的工作是一个很大的挑战
附张图:
以前看的一个数据分析和数据科学的介绍视频截的图: