Data Science Model Deployments and Cloud Computing on GCP - Lab - Deploy Training Code to App Engine

This video tutorial covers deploying an application to Google App Engine, training a machine learning model, and deploying the serialized model to Google Cloud Storage. It explains the setup of necessary files, the main Python script, and the training process, including hyperparameter tuning. The video also demonstrates how to check logs and handle errors, concluding with a preview of serving predictions in the next video.

What is the primary purpose of deploying an application on Google App Engine in this tutorial?

• To create a static website

• To train and deploy a machine learning model

• To develop a mobile application

• To host a database

Which file is NOT mentioned as part of the model training deployment folder?

• requirements.txt

• Dockerfile

• main.py

• app.yaml

Which library is used for serializing the model in the Python script?

• Pandas

• Pickle

• Flask

• GCSFS

What is the default solver used for logistic regression in this tutorial?

• SAGA

• LBFGS

• Newton-CG

• SAG

What command is used to deploy the application on Google Cloud?

• gcloud app deploy

• gcloud compute start

• gcloud app start

• gcloud deploy app

What should you do before executing the Python script for training?

• Set up a VPN

• Create a bucket and upload the CSV file

• Install Docker

• Create a virtual machine

How can you verify that the model has been successfully deployed?

• By running a local server

• By checking the endpoint and logs

• By checking the database

• By opening the model file

What is the purpose of checking logs in the application?

• To manage user access

• To update the application

• To debug the application

• To monitor server uptime

What error is expected if an incorrect solver value is provided?

• Syntax Error

• Connection Timeout

• Internal Server Error

• File Not Found Error

What is suggested as a better way to handle errors in Flask?

• Restarting the server

• Ignoring the error

• Using a try-catch block

• Displaying a user-friendly error message