自動(dòng)化數(shù)據(jù)科學(xué)：平民化

時(shí)間：2022-03-25 10:36:01 | 來源：行業(yè)動(dòng)態(tài)

時(shí)間：2022-03-25 10:36:01 來源：行業(yè)動(dòng)態(tài)

One of the chief benefits of AutoML 2.0 platforms is true data science democratization. When data science automation can accelerate and automate the process of discovering and creating features, it allows for a more diverse and abundant group of users to contribute to the data science process. Automation of feature creation allows the "citizen" data scientist to create incredibly useful, highly optimized use-cases. Because citizen data scientists typically have a high degree of "domain expertise," they can focus on use cases that are of high value to the organization with minimal if any assistance from the data science team. The added benefit of enabling citizen data scientists is that it allows the business to expand their use of data science without having to worry about hiring armies of data scientists. The ability to empower new data science contributors is especially significant given the difficulty organizations in the US have had in hiring data scientists, as examined in[ a 2018 LinkedIn study](https://news.linkedin.com/2018/8/linkedin-workforce- report-august-2018 ). With economic uncertainty facing the global community, enabling a new class of AI/ML developers with minimal investments becomes a game-changing value proposition to maintain or increase competitive advantages.

AutoML 2.0平臺(tái)的主要好處之一是可以用于真正的數(shù)據(jù)科學(xué)平民化。

數(shù)據(jù)科學(xué)自動(dòng)化可以加速發(fā)現(xiàn)要素和創(chuàng)建功能的過程，而且是自動(dòng)的，如此一來，更多的用戶群體就可以為數(shù)據(jù)科學(xué)過程做貢獻(xiàn)。要素創(chuàng)建的自動(dòng)化使得公民數(shù)據(jù)科學(xué)家能夠創(chuàng)建極有用的、高度優(yōu)化的用例。而且公民數(shù)據(jù)科學(xué)家通常具有高度的專業(yè)領(lǐng)域知識(shí)，因此他們基本無需數(shù)據(jù)科學(xué)團(tuán)隊(duì)的幫助就可以將重點(diǎn)放在對(duì)組織具有高價(jià)值的用例上。

開啟公民數(shù)據(jù)科學(xué)家的另一個(gè)好處在于，企業(yè)無需擔(dān)心招不到數(shù)據(jù)科學(xué)家而一樣可以開拓?cái)?shù)據(jù)科學(xué)的使用。2018年 LinkedIn的一項(xiàng)研究表明，美國(guó)的組織在雇用數(shù)據(jù)科學(xué)家方面遇到困難。鑒于此，能夠發(fā)掘新的數(shù)據(jù)科學(xué)貢獻(xiàn)者就顯得尤為重要。

眼下，全球經(jīng)濟(jì)面臨著諸多不確定性，在這種情況下能以最少的投資發(fā)掘出幾類新的AI/ML開發(fā)人員，必將成為改變游戲規(guī)則的價(jià)值主張，在維持或增加競(jìng)爭(zhēng)優(yōu)勢(shì)上意義重大。

**Automating Data Science: Productivity, Not Replacement**