Next Steps

Train an AI Model for Image Classification of Online Product (Red Hat OpenShift) (Latest Version)


You have successfully completed the image classification lab with TensorFlow, and NVIDIA Triton Inference Server on Openshift. The Openshift environment can be used to deploy and test your own GPU applications.

NVIDIA AI Enterprise software suite includes the frameworks and tools needed for best-in-class AI, the same ones you just used in your lab. And since NVIDIA has done the integration and performance optimizations, you can get started with AI easier and faster.

What’s next?

  1. To continue your LaunchPad experience, contact your NVIDIA Account Manager, who was included in your welcome email.

  2. Do you have a team member who would also benefit from LaunchPad? They can fill out this form to get access.

  3. Ready to start your AI journey? Contact your NVIDIA Account rep or NVIDIA Partner. You will need:

    • An NVIDIA AI Enterprise compatible server

    • NVIDIA AI Enterprise software

    • VMware vSphere 7 U2 or later

  4. Need more information? Here are some resources to learn more:


After you have completed the lab, you can use the environment for additional proofs of concepts. A Jupyter lab instance and an SSH console are also accessible via the left navigation pane. The SSH Console can be used to download new datasets to use with the Jupyter notebook.

To clean up your workspace, so that another member of your team can have a go through the lab; run the following commands in your System Console.


helm del image-classification -n classification-namespace

Launch the Helm chart again using the command below.


helm install image-classification image-classification/ -n classification-namespace

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