The world of AutoML has been proliferating over the past few years – and with a recession looming, the notion of automating the development of AI and Machine Learning is bound to become even more appealing. New platforms are available with increased capabilities and more automation. The advent of AI-powered Feature Engineering – which allows users to discover and create features for data science processing automatically – is enabling a whole new approach to data science that, seemingly, threatens the role of the data scientist. Should data scientists be concerned about these developments? What is the role of the data scientist in an automated process? How do organizations evolve because of this new-found automation?
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