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04 Nov 2020

AutoML: Testing the Limits of Sensible Automation

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09:00 AM - 06:00 PM
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100 - 500
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04 Nov 2020

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Newly Listed
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The notion of automating artificial intelligence (AI) has been with us since the early nineties when predictive analytics vendors sought to equip .. Read more business users with math-free, self-service data modeling tools. Since then, it has grown considerably in scope with vendors seeking to automate everything, from preparation of basic data to fine-tuning of complex neural networks – all using AI to automate AI outcomes. Today, automated machine learning (AutoML) - a specific AI automation application - has found a particularly welcome home with enterprise customers who seek to maximize AI without having to invest heavily in a team of data science experts. For these users, AutoML promises to bring AI down from its ivory tower and to put it into the hands of business experts, speeding time to market for transformative, mission-critical AI outcomes, such as fraud detection and predictive maintenance.

Rohini Thakur

Rohini Thakur

AA at Protiviti

New Delhi, India
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