How to Get the Most Out of Red Hat OpenShift* Data Science with Intel® AI Tools

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Data scientists and developers are always on the lookout for new tools and technologies that can make their jobs easier. This article takes a look at how to employ Red Hat OpenShift* Data Science with oneAPI-powered Intel® AI tools and Habana Gaudi* accelerators.

What is Red Hat OpenShift Data Science?

Red Hat OpenShift Data Science is an AI platform that enables data scientists and developers to work together to create, test, and build intelligent applications.

One of the great things about this platform is that it's built on open source, which means that it tracks the innovation occurring in the community for AI projects.

So why is Red Hat OpenShift Data Science of interest?

Because it provides a lot of tools and features that make it easy for data scientists and developers to collaborate, including a unified user experience for data science tools and resources; an integrated pipeline for building, training, and deploying machine learning models; and a flexible deployment architecture for deploying models into production.

Plus, it comes with a ton of libraries and pre-built models that you can use right out of the box.

AND it is a cloud service built on OpenShift, making it easier to deploy models as containers anywhere OpenShift runs—on-prem, on all three major public clouds, and at the edge.

What are Intel® AI Tools & Deep Learning Solutions?

Intel has a suite of AI tools that you can use to get the most out of your data. Here are the top three:

  • Intel® AI Analytics Toolkit provides optimizations for familiar Python* tools and frameworks such as Scikit-learn*, PyTorch*, TensorFlow*, XGBoost* and Modin*, to accelerate end-to-end data science and analytics pipelines on Intel® architectures, maximizing performance—from pre-processing through machine learning—and providing interoperability for efficient data pre-processing model development.
  • Intel® Distribution of OpenVINO™ toolkit allows you to develop and deploy deep learning applications. It includes pre-trained models, development tools, and libraries.
  • Habana Gaudi-based Amazon DL1 instances accelerate model delivery, reduce time-to-train and cost-to train, and make it easy to build new or migrate existing models to Gaudi solutions and deploy them in production environments. Gaudi solutions consist of the Gaudi accelerator and Habana SynapseAI* software suite, optimized for developer ease-of-use of Gaudi and DL1 instances.

Get started using the Red Hat OpenShift Data Science Developer Sandbox

One of the best ways to learn to use Red Hat OpenShift Data Science is to use the developer sandbox. It is:

  • A cloud environment where you can try the AI platform and select Intel® AI portfolio components, including the AI Analytics and OpenVINO toolkits.
  • A great way to test out your code before you put it into production, including trying out different algorithms to see how they work. (There are multiple learning paths such as using Jupyter* Notebooks, importing data from S3, playing with TensorFlow and PyTorch, and even getting started with OpenVINO toolkit.)
  • Easy to use and accessible from any browser.

Why not give it a try?

Tips for Using Red Hat OpenShift Data Science

If you're looking to get the most out of Red Hat OpenShift Data Science and Intel AI, here are some tips to help you out:

  • Check out the tutorials on the Red Hat website. They offer a comprehensive guide to using Red Hat OpenShift Data Science, from installing it to working with datasets.
  • Take advantage of the Intel® AI Developer Program. This program provides access to tools, resources, and training to help you build your own AI applications.
  • Use the forums to ask questions and get help from other users. There's a huge community of people who are happy to share their expertise and help you out.
  • Stay tuned for upcoming events and webinars. Intel and Red Hat offer a range of educational events that can help you learn more about using Red Hat OpenShift Data Science and Intel AI.


Red Hat OpenShift Data Science is a powerful platform for data scientists and developers to build intelligent applications. It is made even better through integrations with Intel AI tools. It's easy to set up and get started, and it provides a lot of flexibility and options for working with Intel-based systems.

Intel has a number of great tools for data science and development, and Red Hat OpenShift Data Science makes it easy to access and use them. The developer sandbox environment is perfect for trying out new tools and techniques, and the built-in support makes it easy to get help when you need it.

If you're looking for a great machine learning platform, try the Red Hat OpenShift Data Science sandbox with Intel AI tools today. It’s hard to beat.

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We would like to thank team RedHat (Christina Xu, Steven Huels, Will McGrath, Audrey Reznik, Leigh Blaylock, Kristin Anderson, Erin Britton, JeffDeMoss) and Team Intel (Susan Lansing, Maya Perry, Ryan Loney, Jack Erikson, Renuke Mendis, Neil Dey, Tony Mongkolsmai, Raghu K Moorthy, Peter Velasquez, Rachel Oberman, Thomas Dewey) for their contributions to the blog and, Monique Torres, Katia Gondarenko, Dan Zloof, Leigh Rosenwald and Keenan Connolly for their review and approval help.

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