BrandPost: How to jump-start machine learning production

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A recent Gartner report found that companies with AI experience were only able to move 53% of their proof-of-concept projects into production over the previous two years. Factors for the stalled projects or outright failures included a lack of machine learning (ML) skills, organizational inertia, and having the right quantity and quality of data for the models.If you’re looking to re-invigorate a stalled ML project, it’s a good idea to take a step back and explore the reasons why you’re stuck.To read this article in full, please click here

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A recent Gartner report found that companies with AI experience were only able to move 53% of their proof-of-concept projects into production over the previous two years. Factors for the stalled projects or outright failures included a lack of machine learning (ML) skills, organizational inertia, and having the right quantity and quality of data for the models.

If you’re looking to re-invigorate a stalled ML project, it’s a good idea to take a step back and explore the reasons why you’re stuck.

To read this article in full, please click here

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