Data Science Model Deployments and Cloud Computing on GCP - Lab - Custom Model Training Using Web Console

This video tutorial demonstrates how to use the Vertex AI web console to train a custom machine learning model. It covers setting up a Jupyter Notebook, creating a service account, uploading necessary files, building a Docker image, and deploying the model to Vertex AI. The tutorial focuses on using logistic regression for model training and provides step-by-step instructions for each process.

What is the purpose of using the web console of Vertex AI?

What files are necessary to upload to the Vertex AI Workbench?

Describe the steps to create a new service account in Vertex AI.

What permissions need to be assigned to the service account?

Explain the process of building a Docker image for the training model.

What is the objective of the machine learning model being trained?

What attributes are included in the input CSV file for the model?

What commands need to be run from the local computer after creating the service account?

How do you deploy a custom job using the web console in Vertex AI?

What is the expected duration for the training job to complete?