How to create a natural language processing (NLP) application using Red Hat OpenShift AI

Learning path | 4 resources | 45 mins | Published on February 8, 2024

In this learning path, created by Evan Shortiss, you are an intern for a transportation department and need to make a list of repairs and organize them. Red Hat OpenShift AI and the Developer Sandbox provide you with the tools and the steps to take, plus free access to a Red Hat OpenShift cluster.

Launch your Developer Sandbox

  1. Overview: How to create a natural language processing (NLP) application using Red Hat OpenShift AI
  2. Access your Developer Sandbox account Page | 15 mins
  3. Clone a GitHub repository into your environment Page | 15 mins
  4. Build the application inside OpenShift Page | 15 mins

Overview: How to create a natural language processing (NLP) application using Red Hat OpenShift AI

AI/MLData SciencePython
Metrobus activity

In this learning path, created by Evan Shortiss, you are an intern for a city transportation department. You have been given the job of processing potential bus repair issues that the drivers have noticed during their shifts. In order to keep the repair issues organized and visible, you need to learn how to categorize them.

Red Hat OpenShift AI provides you with the tools and the steps you'll need to make your repairs possible; the Developer Sandbox for Red Hat OpenShift gives you free access to a Red Hat OpenShift cluster in order to perform this learning path.

Prerequisites

What you’ll be doing

  • Get and/or log in to your Developer Sandbox account
  • Open the Red Hat OpenShift AI session
  • Launch Jupyter
  • Start a notebook server
  • Clone a GitHub repository into your environment
  • Time to play
  • Submitting metro bus repairs using NLP
  • Exposing the model as an API
  • Building the application inside OpenShift
  • Testing the application
  • Conclusion