Data science and machine learning help drive business decisions and generate insights for organizations across a spectrum of industries. But, developing and deploying highly performant machine learning workflows can be challenging. Learn how Intel and Red Hat* partnered to enable AI developer tools from Intel and oneAPI performance optimizations on the Red Hat OpenShift* Data Science platform.

This session shows how to:

• Harness the power of drop-in acceleration for popular frameworks such as TensorFlow* and pandas. Eliminate complex Kubernetes* cloud and infrastructure set up by using Intel® AI Analytics Toolkit on OpenShift.
• Optimize an automatic speech recognition model using OpenVINO™ Development Tools. Then deploy the model in OpenShift using the OpenVINO model server.

Speakers

Audrey Reznik is a senior principal software engineer in the Red Hat Cloud Services - OpenShift Data Science team. She focuses on managed services, AI and machine learning workloads, and next-generation platforms. She has worked in IT for over 20 years in full-stack development and data science roles. Audrey is passionate about data science, in particular the current opportunities with machine learning and open source technologies.

Sean Pryor is a senior software engineer at Red Hat. He integrates independent software vendor (ISV) partners on Open Data Hub and Red Hat Open Data Science.