Machine-learning operations (MLOps) workshop: Object detection models in retail

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In this hands-on webinar, we’ll show you how to efficiently incorporate data science, MLOps, and GitOps into a Red Hat® OpenShift® development workflow.

By taking pictures with your smartphone, you’ll see how applications can use object detection models to find discounted items in a retail store. We’ll follow hypothetical customers as they browse clothing in a department store and use an application to find discounted merchandise.

Join this webinar to learn how to use the Red Hat OpenShift Data Science platform to make application changes and use Red Hat OpenShift Pipelines and GitOps methodologies to rebuild, validate, and redeploy intelligent applications.

Note: We’ll be covering introductory topics in data science, MLOps, and GitOps. All of the work done in each topic will be basic, but if this is your first time with these methodologies, not all of it will be basic to you.

Prior to the webinar, you can sign up to try OpenShift Data Science in the sandbox

During this webinar, you'll:

  • Use Jupyter Notebooks in Red Hat OpenShift Data Science to make changes to the application’s underlying model

  • Use Red Hat OpenShift Pipelines to build and redeploy your intelligent application

  • Manage your application’s health and status using GitOps methodologies with ArgoCD

Live event date:  Thursday, August 25, 2022 | 10 a.m. ET

On-demand event: Available for one year afterward.


Ritesh Shah

Principal Architect, Cloud Technologies, Red Hat

Ritesh Shah is a Principal Architect of Cloud Technologies on the Red Hat Portfolio Technology team focusing on creating and using next-generation platforms, including AI/ML workloads, application modernization and deployment, and software-defined data storage. He has been working in the tech industry for more than 20 years, focusing on systems, platform architecture, and design for deploying various business-critical workloads, including data science.

Ritesh has been an advocate for open source technologies and products, focusing on modern platform architecture and design for critical business needs. He has worked with various customers across industries with a key focus on banking and telecommunication customers. He has been educating various teams, including data scientists, on how to use modern container-based platforms like Red Hat® OpenShift® to cater to the complete life cycle management of intelligent applications using GitOps methodology. Ritesh is passionate about next-generation platforms and how application teams, including data scientists, can use open source technologies to their advantage.

erwan granger

Erwan Granger

Senior Principal Architect, Cloud Services - Red Hat OpenShift Data Science, Red Hat

For the last 20 years, Erwan Granger’s career has brought him both breadth and depth of knowledge as an IT professional. In the pharmaceutical industry, he gained a deep appreciation for the importance of data and analytics. As a consultant and then architect for a large independent software vendor, he developed a passion for identifying and removing unnecessary friction.

Erwan is now a Senior Principal Architect with the Red Hat OpenShift Data Science team. He spends most days applying curiosity and skills to help customers on their Data Science journey.


Cameron Garrison

Software Engineer Intern, Cloud Services - Red Hat OpenShift Data Science, Red Hat

Cameron is a Software Engineer Intern on the Red Hat OpenShift Data Science team. He contributes to workshops, builds synthetic data with generative adversarial networks, and streams simulated real-time data using Apache Kafka. His focus and formal training are primarily on data science and deep learning, with recent interest in application deployment and model life cycle management.