Operational machine learning at enterprise scale
Bring DevOps-like speed and agility to ML workflows with support for every stage of the machine learning lifecycle: from sandbox experimentation with your choice of ML/DL frameworks, to model training on containerized distributed clusters, to deploying and tracking models in production.
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A CONTAINER-BASED SOLUTION FOR THE ML LIFECYCLE
Standardize processes across the ML lifecycle to build, train, deploy, and monitor machine learning models.
What’s New
New Enterprise-Grade Solution for Machine Learning Accelerates AI Innovation
Speed time-to-value for AI projects from months to days and bring DevOps agility to your ML model lifecycle by using new HPE Machine Learning (ML) Ops. ML Ops will transform your AI initiatives from pilot projects to enterprise-grade operations by addressing the entire machine learning lifecycle.
What’s New
New Enterprise-Grade Solution for Machine Learning Accelerates AI Innovation
Speed time-to-value for AI projects from months to days and bring DevOps agility to your ML model lifecycle by using new HPE Machine Learning (ML) Ops. ML Ops will transform your AI initiatives from pilot projects to enterprise-grade operations by addressing the entire machine learning lifecycle.
FASTER TIME TO VALUE FOR AI / ML
HPE (with solutions from BlueData) provides data science teams with one-click deployment for distributed AI / ML environments and secure access to the data they need.