Cloudera Delivers Open Standards Based MLOps

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A new press release states, “Cloudera, the enterprise data cloud company, today announced an expanded set of production machine learning capabilities for MLOps is now available in Cloudera Machine Learning (CML). Organizations can manage and secure the ML lifecycle for production machine learning with CML’s new MLOps features and Cloudera SDX for models. Data scientists, machine learning engineers, and operators can collaborate in a single unified solution, drastically reducing time to value and minimizing business risk for production machine learning models… The release of Cloudera Machine Learning with new MLOps features and Cloudera SDX for models provides a fundamental set of model and lifecycle management capabilities to enable the repeatable, transparent, and governed approaches necessary for scaling model deployments and ML use cases.”

The release goes on, “Benefits include: (1) Unique model cataloging and lineage capabilities allow visibility into the entire ML lifecycle to eliminate silos and blind spots for full lifecycle transparency, explainability and accountability. (2) Full end-to-end machine learning lifecycle management that includes everything required to securely deploy machine learning models to production, ensure accuracy, and scale use cases. (3) A first-class model monitoring service designed to track and monitor both technical aspects and accuracy of predictions in a repeatable, secure, and scalable way. (4) Built on a 100% open source standard and fully integrated with Cloudera Data Platform, enabling customers to integrate into existing and future tooling while not being locked into a single vendor.”

Read more at PR Newswire.

Image used under license from Shutterstock.com

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