Red Hat OpenShift Data Science

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What is Red Hat OpenShift Data Science?

Red Hat® OpenShift® Data Science is an open source machine learning (ML) platform for the hybrid cloud. By providing a fully supported environment to establish MLOps best practices, data scientists and developers can rapidly train, deploy and monitor ML workloads and models on-premise and in the public cloud.

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Preview demo of Red Hat OpenShift Data Science. Video duration: 5:38

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Accelerate your data science

Red Hat OpenShift Data Science allows organizations to quickly build and deploy AI/ML models by integrating open source tooling with commercial partner applications.

The ML models built in Red Hat OpenShift Data Science are easily adaptable to other platforms, allowing teams to deploy them in production, on containers, whether on-premise, at the edge or in the public cloud. Anywhere that OpenShift runs.

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Features & benefits

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Less time managing AI infrastructure

Red Hat OpenShift Data Science provides a flexible environment for data scientists, engineers and developers to build, deploy, and integrate projects faster and more efficiently. Additional time-saving benefits include built-in security and operator life cycle integration.

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Tested and supported AI/ML tooling

Red Hat tracks, integrates, tests, and supports common AI/ML tooling and model serving on our Red Hat OpenShift application platform, so you don’t have to. OpenShift Data Science draws from years of incubation in Red Hat’s Open Data Hub community project.

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Flexibility across the hybrid cloud

Offered as either self-managed software or as a fully managed cloud service on top of OpenShift, Red Hat OpenShift Data Science provides a secure and flexible platform that gives you the choice of where you develop and deploy your models–whether on-premise, the public cloud, or even at the edge.

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Leverage our best practices

Red Hat Consulting and Red Hat Open Innovation Labs provides services that allow you to install, configure and use Red Hat OpenShift Data Science to its fullest extent. 

Learn best practices and build your own ML pipeline project using DevOps and MLOps through Red Hat’s proven methodology.

Expand your capabilities with Red Hat’s partner ecosystem

Improve cross-functional collaboration and simplify maintenance by extending the core Red Hat OpenShift Data Science platform with other integrated Red Hat services and products.

Collaborating through Jupyter notebooks-as-a-service

Provide pre-built or customized cluster images to your data scientists to build models using Jupyter notebooks. Red Hat OpenShift Data Science tracks changes to Jupyter, TensorFlow, and PyTorch, and other open source AI technologies.

Scaling Model Serving with Red Hat OpenShift Data Science

Models can be served for integration into intelligent applications on-premise, in the public cloud or at the edge. These models can be rebuilt, redeployed, and monitored based on changes to the source notebook.

Innovate with open source and hybrid cloud

Red Hat OpenShift Data Science integrates open source tools with Red Hat's AI/ML partner ecosystem to accelerate project development and enhance platform capabilities. Plus, with Red Hat's hybrid cloud approach you can eliminate cloud provider lock-ins and minimize vendor lock-ins.

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Red Hat OpenShift Data Science now available as self-managed

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Top 5 considerations for an AI Platform

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Top 5 ways developers and data scientists can collaborate

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Red Hat OpenShift Data Science Overview

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