Data Science Model Deployments and Cloud Computing on GCP - Lab - Model Training Flow Using Python SDK

The video tutorial guides viewers through the process of mold deployment using Vertex Training Endpoint Deployment SDK. It explains the separation of scripts for model training and deployment for clarity, and demonstrates how to execute these scripts in a Jupyter Notebook. The tutorial includes setting up folders and terminals, executing scripts, handling errors, and running model predictions. The next steps involve Docker image creation and deployment to a local endpoint.

What is the purpose of separating the scripts into model training and deployment?

Describe the process of running the model training script as mentioned in the text.

What is the significance of the 'pipeline component' in the script?

Explain the error encountered when running the script and how it was resolved.

What are the expected outputs when running a prediction against test values?