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Operationalize Machine Learning

July 13, 2020

Machine learning (ML) is the catalyst for a strong, flexible, and resilient business in today’s market. Smart companies leverage ML to create top-to-bottom growth, employee productivity, and customer satisfaction.

In order to successfully achieve ML at scale, firms must invest in MLOps—the process, tools, and technology that streamline and standardize each stage of the ML life cycle from model development to operationalization.

In March 2020, HPE and Intel commissioned Forrester Consulting to evaluate machine learning initiatives across enterprises. Forrester conducted an online survey of 162 respondents with ML responsibilities at companies with 5,000 or more employees to explore this topic.

The findings reveal that companies expect machine learning use cases to increase business success, but they are struggling to implement ML at scale—and their MLOps capabilities are relatively immature.

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