One of the greatest challenges to using AI/ML in industry is reducing your time to solution so that your data scientist and engineers have a chance to iterate. Setting up a machine learning pipeline from scratch can be a complexity nightmare for MLOps engineers.

Steve Huels and Raghu Moorthy join Tony to discuss the value of RedHat OpenShift Data Science, how the platform is built, and how it can significantly reduce the initial deployment challenge. They also discuss some of the software deployed as part of the RedHat OpenShift Data Science platform and how these pieces drive cost effective, accelerated AI solutions from Cloud to Edge.

Intel-Redhat Partner page:
intel.com/content/www/us/en/developer/partner/red-hat.html

Open Data Hub:
opendatahub.io

RedHat Open Shift Data Science Sandbox:
developers.redhat.com/products/red-hat-openshift-data-science/getting-started

Guests:
Steve Huels – Senior Director for Red Hat’s Cloud Services
redhat.com/en/authors/steven-huels

Raghu Moorthy – Global Director Intel Sales and Marketing Group:
linkedin.com/in/raghunath-k-moorthy

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Tags: AI, AI/ML, artificial intelligence, Data Science, developers, Flex GPU, Habana, Hardware Accelerators, Hybrid Cloud, Intel, Jupyter, JupyterHub, JupyterLab, machine learning, MLOps, oneAPI, Open Data Hub, Open Source, OpenShift, OpenShift Data Science, Pytorch, Raghu Moorthy, Red Hat, Steve Huels, TensorFlow
 
Posted in: Audio Podcast, Cloud Computing, Code Together, Intel