Winter Special Limited Time 65% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: bigdisc65

Free Access Google Professional-Machine-Learning-Engineer New Release

Page: 20 / 21
Question 80

You have deployed multiple versions of an image classification model on Al Platform. You want to monitor the performance of the model versions overtime. How should you perform this comparison?

Options:

A.

Compare the loss performance for each model on a held-out dataset.

B.

Compare the loss performance for each model on the validation data

C.

Compare the receiver operating characteristic (ROC) curve for each model using the What-lf Tool

D.

Compare the mean average precision across the models using the Continuous Evaluation feature

Question 81

You are an ML engineer at a mobile gaming company. A data scientist on your team recently trained a TensorFlow model, and you are responsible for deploying this model into a mobile application. You discover that the inference latency of the current model doesn’t meet production requirements. You need to reduce the inference time by 50%, and you are willing to accept a small decrease in model accuracy in order to reach the latency requirement. Without training a new model, which model optimization technique for reducing latency should you try first?

Options:

A.

Weight pruning

B.

Dynamic range quantization

C.

Model distillation

D.

Dimensionality reduction

Question 82

You recently joined an enterprise-scale company that has thousands of datasets. You know that there are accurate descriptions for each table in BigQuery, and you are searching for the proper BigQuery table to use for a model you are building on AI Platform. How should you find the data that you need?

Options:

A.

Use Data Catalog to search the BigQuery datasets by using keywords in the table description.

B.

Tag each of your model and version resources on AI Platform with the name of the BigQuery table that was used for training.

C.

Maintain a lookup table in BigQuery that maps the table descriptions to the table ID. Query the lookup table to find the correct table ID for the data that you need.

D.

Execute a query in BigQuery to retrieve all the existing table names in your project using the

INFORMATION_SCHEMA metadata tables that are native to BigQuery. Use the result o find the table that you need.

Question 83

You work for a hospital that wants to optimize how it schedules operations. You need to create a model that uses the relationship between the number of surgeries scheduled and beds used You want to predict how many beds will be needed for patients each day in advance based on the scheduled surgeries You have one year of data for the hospital organized in 365 rows

The data includes the following variables for each day

• Number of scheduled surgeries

• Number of beds occupied

• Date

You want to maximize the speed of model development and testing What should you do?

Options:

A.

Create a BigQuery table Use BigQuery ML to build a regression model, with number of beds as the target variable and number of scheduled surgeries and date features (such as day of week) as the predictors

B.

Create a BigQuery table Use BigQuery ML to build an ARIMA model, with number of beds as the target variable and date as the time variable.

C.

Create a Vertex Al tabular dataset Tram an AutoML regression model, with number of beds as the target variable and number of scheduled minor surgeries and date features (such as day of the week) as the predictors

D.

Create a Vertex Al tabular dataset Train a Vertex Al AutoML Forecasting model with number of beds as the target variable, number of scheduled surgeries as a covariate, and date as the time variable.

Page: 20 / 21
Exam Name: Google Professional Machine Learning Engineer
Last Update: Nov 22, 2024
Questions: 285
Professional-Machine-Learning-Engineer pdf

Professional-Machine-Learning-Engineer PDF

$29.75  $84.99
Professional-Machine-Learning-Engineer Engine

Professional-Machine-Learning-Engineer Testing Engine

$33.25  $94.99
Professional-Machine-Learning-Engineer PDF + Engine

Professional-Machine-Learning-Engineer PDF + Testing Engine

$47.25  $134.99