Artificial intelligence and machine learning (ML) applications are becoming increasingly popular, however the process for developing, deploying, and continuously improving them is complex. As per VentureBeat report, 87% of projects never make it into production. MLOps extends DevOps into the machine learning space. MLOps refers to the culture where people, regardless of their title or background, work together to imagine, develop, deploy, operate, and improve a machine learning system.
This whitepaper outlines the challenge of productionizing ML, explains some best practices, and presents solutions. Thoughtworks introduces the idea of MLOps as continuous delivery for machine learning. The rest of the whitepaper details solutions from AWS and other partners.
A key enabler of Nimble's brand promise of "Making Finance Faster" is the adoption and implementation of an industrialized ML capability. Find out more about their transformation.
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