Red Hat OpenShift Data Science Workshop - Object Detection

Introduction

Welcome!

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 in several different ways.

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

And 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.

Environment

If you haven’t already got an instance of Red Hat OpenShift Data Science, find out more on the developer page. There, you can spin up your own account on the free OpenShift Data Science Sandbox or learn about installing on your own OpenShift cluster.

Videos

If you’d like to follow along with the accompanying videos of this workshop, you can find them in the article on the Red Hat Developer website or watch on YouTube
 

Start!

If you’re ready, let’s start!