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Lab 7: Integrate Machine Learning Model with a Sample Application

In this hands-on lab, we get to use the model we’ve created and the online deployment we configured for it. We will see how that endpoint can be called from a sample Python application to get model predictions.

You will integrate your specific model endpoint to the sample application and can choose to either run the application locally or deploy it to the IBM Cloud.

For the lab, you will be following these lab instructions

Javier Torres

Developer Advocate

Javier Torres is a developer advocate and senior software engineer with IBM. He engages with customer and partner development teams to enable them on Cloud & Artificial Intelligence technologies. Prior to this role, he was a Solution Architect focusing on IBM Watson technologies. Javier has more than 15 years experience and holds a Masters degree in Computer Science. He is currently interested in topics related to machine learning, deep learning, information retrieval and learning new development languages/technologies. Outside of technology and work; Javier enjoys spending time with his wife and daughter, and being active outdoors.