Parkinson Detector App Deployment Part2 iBest Workshop
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Continue the development of the Parkinson’s detector app in Part 2 of the iBest workshop. Learn how to deploy your app and make it accessible for real-world use, enhancing Parkinson’s diagnosis.
At a Glance
Do you want to deploy a serverless AI model like a software engineer using technologies such as Docker containers and Kubernetes? This guided project will show you how to deploy a Parkinson detection app in 10 mins. On the one hand, this project does not require knowledge of front-end and back-end development. On the other hand, the model deployment comes at no cost! You get free resources on IBM Cloud to experiment with deploying the AI model you like and share the app.
Parkinson detection app
Learning Objectives
- Know how to wrap a Machine Learning model inside Gradio’s interface.
- Understand containerization.
- Have hands-on experience with containerization.
- Become familiar with IBM Code Engine.
- Know how to use Code Engine to create and store container images on IBM Cloud.
- Deploy the Machine Learning app from the container image.
- Learn good practices and troubleshooting with IBM Code Engine.
Prerequisites (optional)
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