OpenShift Data Science workshop: Object detection for retail

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In this workshop, you’ll learn how to efficiently incorporate data science, artificial intelligence, and machine learning (AI/ML) into an OpenShift® development workflow. Using our smartphone to assign a coupon value to any sale item, you’ll use an object detection model to detect items discounted in a retail store.

We’ll allow hypothetical customers to find merchandise discounts, such as shirts, as they browse clothing in a department store.

Also, build an app that will display a discount, such as a coupon.

This workshop will build an app that uses a picture of clothing and determines if a shirt is present that qualifies for a discount.

Learn how to install anything on your computer using Red Hat® OpenShift Data Science and Red Hat OpenShift Streams for Apache Kafka.  

Note: Beginner data handling and python skills are required for this workshop.  

Prior to the workshop, please sign up for Red Hat OpenShift Data Science developer to  try OpenShift Data Science in the sandbox.

During this workshop, you will:

  • Use Jupyter Notebooks and TensorFlow to explore a pretrained object detection model
  • Use source-to-image (S2I) to build and deploy your intelligent application
  • Deploy an Apache Kafka consumer with the same object detection model

Live event date: Thursday, July 21, 2022 | 10 a.m. ET 

On-demand event: Available for one year afterward.


Audrey Reznik

Senior Principal Software Engineer, Cloud Services - Red Hat OpenShift Data Science, Red Hat

Audrey Reznik is a Senior Principal Software Engineer focusing on managed services, AI/ML workloads and, next-generation platforms. She has been working in the IT Industry for more than 20 years in full stack development to data science roles. 

As a former technical advisor and data scientist, Audrey has been educating data scientists and developers about Red Hat OpenShift platform and how to use Red Hat OpenShift containers (images) to organize, develop, train and deploy intelligent applications using the machine learning model operationalization management (MLOps). She is passionate about data science and, in particular, the current opportunities with ML and open source technologies.

Ritesh Shah

Ritesh Shah

Principal Architect, Cloud Technologies, Red Hat

Ritesh is a Principal Architect, Cloud Technologies in 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 evangelist 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. He is passionate about next-generation platforms and how application teams, including data scientists, can use open source technologies to their advantage.