Free Access Google.Professional-Machine-Learning-Engineer.v2023-02-27.q25 Practice Test (Page 2)

Question 1

Your team is working on an NLP research project to predict political affiliation of authors based on articles they have written. You have a large training dataset that is structured like this:

A.Option A

B.Option B

C.Option C

D.Option D

Question 2

Your organization wants to make its internal shuttle service route more efficient. The shuttles currently stop at all pick-up points across the city every 30 minutes between 7 am and 10 am. The development team has already built an application on Google Kubernetes Engine that requires users to confirm their presence and shuttle station one day in advance. What approach should you take?

A.1. Build a tree-based regression model that predicts how many passengers will be picked up at each shuttle station.
2. Dispatch an appropriately sized shuttle and provide the map with the required stops based on the prediction.

B.1. Build a tree-based classification model that predicts whether the shuttle should pick up passengers at each shuttle station.
2. Dispatch an available shuttle and provide the map with the required stops based on the prediction

C.1. Define the optimal route as the shortest route that passes by all shuttle stations with confirmed attendance at the given time under capacity constraints.
2 Dispatch an appropriately sized shuttle and indicate the required stops on the map

D.1. Build a reinforcement learning model with tree-based classification models that predict the presence of passengers at shuttle stops as agents and a reward function around a distance-based metric
2. Dispatch an appropriately sized shuttle and provide the map with the required stops based on the simulated outcome.

Question 3

You are training a TensorFlow model on a structured data set with 100 billion records stored in several CSV files. You need to improve the input/output execution performance. What should you do?

A.Load the data into BigQuery and read the data from BigQuery.

B.Convert the CSV files into shards of TFRecords, and store the data in Cloud Storage

C.Load the data into Cloud Bigtable, and read the data from Bigtable

D.Convert the CSV files into shards of TFRecords, and store the data in the Hadoop Distributed File System (HDFS)

Question 4

You are going to train a DNN regression model with Keras APIs using this code:

How many trainable weights does your model have? (The arithmetic below is correct.)

A.501*256+257*128+2 = 161154

B.501*256+257*128+128*2=161408

C.500*256*0 25+256*128*0 25+128*2 = 40448

D.500*256+256*128+128*2 = 161024

Question 5

You are developing ML models with Al Platform for image segmentation on CT scans. You frequently update your model architectures based on the newest available research papers, and have to rerun training on the same dataset to benchmark their performance. You want to minimize computation costs and manual intervention while having version control for your code. What should you do?

A.Use Cloud Functions to identify changes to your code in Cloud Storage and trigger a retraining job

B.Use the gcloud command-line tool to submit training jobs on Al Platform when you update your code

C.Use Cloud Build linked with Cloud Source Repositories to trigger retraining when new code is pushed to the repository

D.Create an automated workflow in Cloud Composer that runs daily and looks for changes in code in Cloud Storage using a sensor.

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