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技术

Automated machine learning (AutoML)

NOT ON THE CURRENT EDITION
This blip is not on the current edition of the radar. If it was on one of the last few editions it is likely that it is still relevant. If the blip is older it might no longer be relevant and our assessment might be different today. Unfortunately, we simply don't have the bandwidth to continuously review blips from previous editions of the radarUnderstand more
Nov 2019
试验?

机器学习的强大能力和远大前途使得对专业人才的需求远远超出了专门从事该领域的数据科学家的数目。针对这种技能上的差距,我们看到了自动化机器学习AutoML)工具的出现,这类工具旨在帮助非专业人士更容易地自动化完成从模型选择到模型训练的端到端过程。比如Google的AutoMLDataRobotH2O AutoML Interface。尽管我们已经从这些工具中看到了可喜的成果,但还是要提醒企业不要将其视为机器学习旅程的全部。如H2O网站所述,“在数据科学领域,仍需要相当深厚的知识和经验才能产出高性能的机器学习模型”。对自动化技术的盲目信任,还会增加引入道德偏见或做出不利于少数群体的决策风险。虽然企业可以使用这些工具作为起点,生成基本有用的经过训练的模型,但我们还是鼓励他们寻找经验丰富的数据科学家来验证和完善最终的模型。