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Learn more about accelerating data science with self-service

Hit the high points with this summary discussion on analytics model deployment model challenges and solutions provided by containers like HPE Ezmeral Container Platform. Then read the deep-dive blog for more insights—and get the details on an upcoming webinar on self-service data science and GPU optimization.

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While organizations are eager to adopt and reap the benefits of AI, they are facing challenges that make developing and deploying analytic models painfully slow. One viable solution lies in leveraging self-service to accelerate the process.

A new blog on HPE Ezmeral: Uncut explores the factors contributing to data science bottlenecks—including lack of team coordination and resource utilization—and outlines how containers offer a solution.

In particular, HPE Ezmeral Container Platform is designed to accelerate the deployment of containerized applications at scale running on any infrastructure, It’s a hybrid cloud platform that brings speed, agility, and ease to data science. Built on 100% open source Kubernetes, HPE Ezmeral Container Platform gives users the flexibility to build and deploy Kubernetes clusters across the hybrid IT landscape and manage them from a unified control plane. This means big challenges like long infrastructure provision times and the misallocation of resources like GPUs can be solved if the infrastructure and resources can all be managed from one unified control plane providing visibility and management through self-service across the organization.

With HPE Ezmeral Container Platform, data scientists can enjoy the ease and agility of self-service. From a unified control plane, users can choose their own tools, applications, and storage needs for the job. They can also spin up GPU-accelerated clusters to provision their environments in minutes, instead of months—eliminating delay and wait times at the various handoff points throughout the ML lifecycle.

Self-service is welcome across industries

By enabling self-service in the provisioning of infrastructure and resources like GPUs, organizations benefit from improved compute performance, lower infrastructure costs through the efficient use of resources, and increased productivity of their data scientists. They can now unleash the power of AI to uncover insights into customer behavior and what is happening in the world around us. Businesses, government agencies, and organizations across industries – from healthcare, financial services, and manufacturing to retail—can respond to customer needs, diagnose diseases, discover drug treatments, detect fraud, and prevent security breaches—quickly and accurately.

For more insights and deeper details, read the complete blog here: Analytic model deployment too slow? Accelerate data science with self-service.

Still interested in learning more about how HPE Ezmeral simplifies infrastructure management and modernizes data science? Register in advance to attend our upcoming World Watch webinar on February 17: Self-Service Data Science and GPU Optimization.

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TechExperts

Our team of HPE and other technology experts shares insights about relevant topics related to artificial intelligence, data analytics, IoT, and telco.

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