Why 87% of Machine learning Projects Fail

Written by Prajeen Vijayan | Published 2020/09/14
Tech Story Tags: data-science | machine-learning | artificial-intelligence | data-strategy | why-ml-projects-fail | top-10-reasons | ai | ml | web-monetization

TLDR Why 87% of Machine learning Projects Fail? Here are 10 reasons why. Gartner’s predictions, “Through 2020, 80% of AI projects will remain alchemy, run by wizards whose talents will not scale in the organization” VentureBeat predicted that 87% will never make it into production. Organizations are still unfamiliar with the software tools and the required hardware. The technology is still new to a large audience. Experienced data scientists are needed to handle most of the success criteria, final deployment and continuous monitoring.via the TL;DR App

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Written by Prajeen Vijayan | Data Scientist | Product Manager | https://breakdowndata.com/
Published by HackerNoon on 2020/09/14