Object Detection with Red Hat OpenShift Data Science


In this workshop, you’ll learn an easy way to incorporate data science and AI/ML into an OpenShift development workflow. As an example, you’ll use an object detection model to detect ‘dog(s)’ in an image.

You will:
Use Jupyter Notebooks and TensorFlow to explore a pre-trained object detection model
Serve the model in a REST API as a Flask App
Use Source-to-Image (S2I) to build and deploy the Flask app
Explore Kafka streams from Notebooks
Deploy a Kafka consumer with the same object detection model

You’ll be able to do all of this without having to install anything on your own computer, thanks to Red Hat OpenShift Data Science and Red Hat OpenShift Streams for Apache Kafka.

Background Knowledge
Note: Beginner data handling and Python skills are required for this workshop.
*Prior to the workshop, please sign up for RHODS Sandbox access at: Start using your OpenShift Data Science sandbox (https://developers.redhat.com/products/red-hat-openshift-data-science/overview)


Prasanth Anbalagan is a Senior Principal Software Engineer (QE and Analysis) on the Red Hat OpenShift Data Science team. Prasanth earned his M.S and Ph.D in Computer Science from North Carolina State University focusing on Software Reliability Engineering, Predictive Modeling and Automated Software Engineering. As a member of AI team at Red Hat, Prasanth focuses on development of services and tools to analyze, manipulate, and visualize data and execute automated operations as part of an Analytics, Machine Learning and AI platform.

Open Data Science




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