AutoML: Bridging the skills gap with machine learning

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AutoML is seeing a wave of new progress and paving the way to bridging an urgent skills gap.

16 September 2020

Machine learning and AutoML is bridging the skills gap by designing its own technology. Source: Shutterstock

Early adopters of data science automation tools across industries are reporting significant time and cost savings as well as revenue gains
The number of firms investing in big data and AI has ballooned to 33.9% from 27% in 2018
More than 40% of data science tasks are expected to be automated in 2020

Is there anything that can stop AI? As the novel Covid-19 pandemic forces the world to put on its brakes, AI technologies like machine learning – AutoML in particular – have been continuing to develop at break-neck speeds at the beginning of the new decade.
Following a recent breakthrough by Google scientists at the start of a period of enforced lockdown, AutoML is seeing a wave of new progress in correlation with the explosion of big data, advanced analytics and predictive models. The increasing amount of viable data has meant that AI, machine learning (ML) and data science is undergoing reams of data and training that has served to boost the technology exponentially.
AutoML in 2020, can perform data pre-processing, …

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