- Community Home
- >
- Solutions
- >
- Tech Insights
- >
- Learn more about accelerating data science with se...
Categories
Company
Local Language
Forums
Discussions
Forums
- Data Protection and Retention
- Entry Storage Systems
- Legacy
- Midrange and Enterprise Storage
- Storage Networking
- HPE Nimble Storage
Discussions
Discussions
Discussions
Forums
Forums
Discussions
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
- BladeSystem Infrastructure and Application Solutions
- Appliance Servers
- Alpha Servers
- BackOffice Products
- Internet Products
- HPE 9000 and HPE e3000 Servers
- Networking
- Netservers
- Secure OS Software for Linux
- Server Management (Insight Manager 7)
- Windows Server 2003
- Operating System - Tru64 Unix
- ProLiant Deployment and Provisioning
- Linux-Based Community / Regional
- Microsoft System Center Integration
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Discussion Boards
Community
Resources
Forums
Blogs
- Subscribe to RSS Feed
- Mark as New
- Mark as Read
- Bookmark
- Receive email notifications
- Printer Friendly Page
- Report Inappropriate Content
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 insightsโand get the details on an upcoming webinar on self-service data science and GPU optimization.
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 bottlenecksโincluding lack of team coordination and resource utilizationโand 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, Itโs 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 monthsโeliminating 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 โ from healthcare, financial services, and manufacturing to retailโcan respond to customer needs, diagnose diseases, discover drug treatments, detect fraud, and prevent security breachesโquickly 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.
- Back to Blog
- Newer Article
- Older Article
- Amy Saunders on: Smart buildings and the future of automation
- Sandeep Pendharkar on: From rainbows and unicorns to real recognition of ...
- Anni1 on: Modern use cases for video analytics
- Terry Hughes on: CuBE Packaging improves manufacturing productivity...
- Sarah Leslie on: IoT in The Post-Digital Era is Upon Us โ Are You R...
- Marty Poniatowski on: Seamlessly scaling HPC and AI initiatives with HPE...
- Sabine Sauter on: 2018 AI review: A year of innovation
- Innovation Champ on: How the Internet of Things Is Cultivating a New Vi...
- Bestvela on: Unleash the power of the cloud, right at your edge...
- Balconycrops on: HPE at Mobile World Congress: Creating a better fu...
-
5G
2 -
Artificial Intelligence
101 -
business continuity
1 -
climate change
1 -
cyber resilience
1 -
cyberresilience
1 -
cybersecurity
1 -
Edge and IoT
97 -
HPE GreenLake
1 -
resilience
1 -
security
1 -
Telco
108