自動化數(shù)據(jù)科學(xué)：生產(chǎn)力而非替代

時間：2022-03-25 11:15:02 | 來源：行業(yè)動態(tài)

時間：2022-03-25 11:15:02 來源：行業(yè)動態(tài)

Any conversation of AutoML 2.0 platforms, however, is misplaced if the focus is on replacing or displacing the data scientist. Most data scientists see feature-engineering as one of the most significant obstacles to their work. Automation can only help to accelerate the process by providing incredible productivity boosts that would not be otherwise possible without automation. By leveraging AutoML 2.0, data scientists can often accelerate their work dramatically - from months to days. Besides, the use of AI-based feature engineering in AutoML 2.0 platforms, allows data scientists to discover features that they would have never considered. AI-based feature engineering automatically builds, evaluates, and exposes features by combining data from multiple columns, often across different tables and sources. The ability of AutoML 2.0 to self-discover features allows data scientists to explore the so- called "unknown unknowns," the features the data scientists would have never even considered because of either lack of time or lack of domain expertise.

但任何AutoML 2.0平臺如果將定位的重點放在替換或更替數(shù)據(jù)科學(xué)家上就大錯特錯了。大多數(shù)數(shù)據(jù)科學(xué)家都將要素工程視為工作中的最大障礙之一。自動化可以幫助加快要素工程的流程，靠的就是自動化可以提供令人難以置信的生產(chǎn)率提升，這種提升若無自動化是不可能實現(xiàn)的。

對于數(shù)據(jù)科學(xué)家來說，利用AutoML 2.0通?？梢詷O大地加快自己的工作，縮短的工作時間從幾天到幾個月不等。而且，數(shù)據(jù)科學(xué)家在AutoML 2.0平臺上使用基于AI的要素工程還可以發(fā)現(xiàn)他們從未考慮過的要素?；贏I的要素工程可以自動構(gòu)建、評估和開通要素，而且可以結(jié)合來自基于多列的數(shù)據(jù)（通常是跨越不同的表和源）。

此外，AutoML 2.0還具有自我發(fā)現(xiàn)要素的功能，數(shù)據(jù)科學(xué)家借此功能可以探索所謂的未知的未知數(shù)，這種未知的未知數(shù)屬于那些數(shù)據(jù)科學(xué)家由于缺乏時間或缺乏領(lǐng)域?qū)I(yè)知識而從未考慮過的要素。

**AutoML 2.0: Creating A More Productive, More Inclusive AI/ML Program**