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 containerised distributed clusters, to deploying and tracking models in production.
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A CONTAINER-BASED SOLUTION FOR THE ML LIFECYCLE
Standardise processes across the ML lifecycle to build, train, deploy and monitor machine learning models.
Model Deployment and Monitoring
Security and Control
- 53increased profitability 1
- 52better customer experience 2
- 49better adoption of data science best practices 3
Now available on-demand, see how to run, manage, control and secure apps, data and IT operations that run your business. Learn how HPE Ezmeral software runs containers and Kubernetes at scale to modernize apps, from edge to cloud.
“Our online games generate billions of data points every day. Using complex ML models, our data scientists leverage this data for prescriptive analytics to improve our players’ experience, lifetime value and loyalty. With HPE’s BlueData software, we’re containerising these ML and analytics environments to help improve operational efficiency and optimise our business.”Alex Ryabov, Head of Data Services, Wargaming
FASTER TIME TO VALUE FOR AI / ML
HPE provides data science teams with one-click deployment for distributed AI / ML environments and secure access to the data they need.
HPE Ezmeral ML Ops
A software solution that extends the capabilities of the HPE Ezmeral Container platform to support the entire machine learning lifecycle and implement DevOps like processes to standardise machine learning workflows.
ADVISORY BOARD (OPTUM) USES BLUEDATA TO ACCELERATE BUSINESS OUTCOMES WITH AI AND ML IN THE ENTERPRISE
Advisory Board (Optum) deploys predictive analytics and machine learning on big data using the container-based platform from HPE’s BlueData team platform. Learn how they streamlined operations and cut costs while enhancing patient care in U.S. hospitals.
Helping hospitals across the US translate their big data into actionable insights that deliver business value.
Deployment of distributed ML and analytics applications and for the separation of compute and memory from storage.
“BlueData has helped us to address these challenges with their containerised solution that has delivered faster time-to-insights, reduced our costs and freed up our staff to innovate. It’s paying big dividends for our organisation, and we look forward to continuing our journey together.”
Data-driven insights needed to improve operational efficiency, reduce infrastructure costs and enhance patient care.
Operationalising Machine Learning
This webinar with experts from HPE and Forrester Research looks at the key technological and organisational challenges that impact the success of machine learning (ML) projects.