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 primary focus of using the Vertex AI web console in this tutorial?

• To manually train a machine learning model

• To learn about SDK integration

• To explore pre-built models

• To understand cloud storage

Why is creating a service account important before starting with Vertex AI?

• It helps in data visualization

• It allows for model deployment

• It is necessary for managing permissions

• It provides access to Google Drive

Which files are essential to upload to the Jupyter notebook for this tutorial?

• Image files, video files, and audio files

• Python script, HTML file, and CSS file

• CSV file, JSON file, and XML file

• Docker file, model training file, and requirements.txt

What is the base image used in the Docker file?

• Python 3.10 slim

• Ubuntu 20.04

• Node.js 14

• Java 11

What is the purpose of the Docker build command in this tutorial?

• To build a Docker image from the Docker file

• To create a new Jupyter notebook

• To upload files to Google Cloud Storage

• To delete existing Docker images

What role is assigned to the service account for accessing Google Cloud Storage?

• Admin role

• Custom role

• Editor role

• Viewer role

What is the final step before deploying the model to Vertex AI?

• Running the Docker image locally

• Creating a new service account

• Deleting the model artifact

• Uploading the CSV file

Which machine type is selected for training the model in Vertex AI?

• East one, standard 8

• West one, standard 6

• South one, standard 2

• North one, standard 4

What is the expected duration for the training process in Vertex AI?

• 15-20 minutes

• 9-10 minutes

• 5-6 minutes

• 1-2 minutes

What is the purpose of the 'no prediction container' option during deployment?

• To enhance training speed

• To skip model serving setup

• To focus on model serving

• To enable hyperparameter tuning