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Why ML Projects Fail and How to Ensure Their Success

Автор: The TWIML AI Podcast with Sam Charrington

Загружено: 2022-09-07

Просмотров: 109

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Recent Gartner research pegged the failure rate of data and AI projects at 60-85%. There are many reasons why AI projects fail, but the question remains: What can leaders do to increase the success rate of ML/AI projects? This panel discussion will explore the principles, processes and practices that allow teams to get more models, with greater impact, launched and into production more quickly and consistently.

Why ML Projects Fail and How to Ensure Their Success

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