Deploying ML Web App on Google Kubernetes Engine -Autopilot
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Overview
By the end of this project, we will be having a hands-on practical experience of creating a Google cloud project, running dog breed classification Streamlit web app locally, creating a docker image of our machine learning web app and saving it in Google Container Registry (GCR), creating a GKE-Autopilot cluster, creating a Kubernetes deployment and service, testing the web app running on GKE-Autopilot and finally, deleting the project to avoid incurring charges to our Google Cloud account.
Taught by
Muhammad Ali