Data Science Model Deployments and Cloud Computing on GCP - Lab - Model Endpoint Deployment

The video tutorial provides a recap of previous lessons on mole training using the web console and Python SDK. It introduces the process of uploading models to a Vertex AI registry and deploying them to an endpoint for online and batch predictions. The tutorial explains the folder structure, including key files like predictor.py and requirements.txt. It outlines the steps for training a model, deploying it as a Docker image to a local endpoint, and finally uploading it to a Vertex AI model registry for deployment. The video concludes with running predictions against the deployed model.

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