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Training AutoML Models Using Vertex AI

Authored by Jake Catron

Instructional Technology

Professional Development

Training AutoML Models Using Vertex AI
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9 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

For a user who can use SQL, has little Machine Learning experience and wants a ‘Low-Code’ solution, which Machine Learning framework should they use?

AutoML

Python

Scikit-Learn

BigQuery ML

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following metrics can be used to find a suitable balance between precision and recall in a model?

F1 Score

ROC AUC

Log Loss

PR AUC

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the default setting in AutoML Tables for the data split in model evaluation?

80% Training, 15% Validation, 5% Testing

80% Training, 5% Validation, 15% Testing

70% Training, 20% Validation, 10% Testing

80% Training 10% Validation, 10% Testing

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following are stages of the Machine Learning workflow that can be managed with Vertex AI?

Create a dataset and upload data.

Train an ML model on your data

All of the options

Deploy your trained model to an endpoint for serving predictions.

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does the Feature Importance attribution in Vertex AI display?

How much each feature impacts the model, expressed as a ranked list

How much each feature impacts the model, expressed as a percentage

How much each feature impacts the model, expressed as a decimal

How much each feature impacts the model, expressed as a ratio

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main benefit of using an automated Machine Learning workflow?

It makes the model run faster

It deploys the model into production

It reduces the time it takes to develop trained models and assess their performance

It makes the model perform better

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

MAE, MAPE, RMSE, RMSLE and R2 are all available as test examples in the Evaluate section of Vertex AI and are common examples of what type of metric?

Decision Trees Progression Metrics

Linear Regression Metrics

Clustering Regression Metrics

Forecasting Regression Metrics

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