最新的Google Cloud Certified認證 Professional-Machine-Learning-Engineer考試題庫

問題1

You are developing a Kubeflow pipeline on Google Kubernetes Engine. The first step in the pipeline is to issue a query against BigQuery. You plan to use the results of that query as the input to the next step in your pipeline. You want to achieve this in the easiest way possible. What should you do?

A. Use the BigQuery console to execute your query and then save the query results Into a new BigQuery table.

B. Locate the Kubeflow Pipelines repository on GitHub Find the BigQuery Query Component, copy that component ' s URL, and use it to load the component into your pipeline. Use the component to execute queries against BigQuery

C. Use the Kubeflow Pipelines domain-specific language to create a custom component that uses the Python BigQuery client library to execute queries

D. Write a Python script that uses the BigQuery API to execute queries against BigQuery Execute this script as the first step in your Kubeflow pipeline

正確答案: B

說明：（僅 VCESoft 成員可見）

問題2

You work for an international manufacturing organization that ships scientific products all over the world Instruction manuals for these products need to be translated to 15 different languages Your organization ' s leadership team wants to start using machine learning to reduce the cost of manual human translations and increase translation speed. You need to implement a scalable solution that maximizes accuracy and minimizes operational overhead. You also want to include a process to evaluate and fix incorrect translations. What should you do?

A. Create a Vertex Al pipeline that processes the documents1 launches an AutoML Translation training job evaluates the translations, and deploys the model to a Vertex Al endpoint with autoscaling and model monitoring When there is a predetermined skew between training and live data re-trigger the pipeline with the latest data.

B. Use Vertex Al custom training jobs to fine-tune a state-of-the-art open source pretrained model with your data Deploy the model to a Vertex Al endpoint with autoscaling and model monitoring When there is a predetermined skew between the training and live data, configure a trigger to run another training job with the latest data.

C. Create a workflow using Cloud Function Triggers Configure a Cloud Function that is triggered when documents are uploaded to an input Cloud Storage bucket Configure another Cloud Function that translates the documents using the Cloud Translation API and saves the translations to an output Cloud Storage bucket Use human reviewers to evaluate the incorrect translations.

D. Use AutoML Translation to tram a model Configure a Translation Hub project and use the trained model to translate the documents Use human reviewers to evaluate the incorrect translations

正確答案: D

說明：（僅 VCESoft 成員可見）

問題3

You work for a company that sells corporate electronic products to thousands of businesses worldwide. Your company stores historical customer data in BigQuery. You need to build a model that predicts customer lifetime value over the next three years. You want to use the simplest approach to build the model. What should you do?

A. Create a Vertex Al Workbench notebook. Use IPython magic to run the create model statement to create an ARIMA model.

B. Access BigQuery Studio in the Google Cloud console. Run the create model statement in the SQL editor to create an AutoML regression model.

C. Access BigQuery Studio in the Google Cloud console. Run the create model statement in the SQL editor to create an ARIMA model.

D. Create a Vertex Al Workbench notebook. Use IPython magic to run the create model statement to create an AutoML regression model.

正確答案: B

說明：（僅 VCESoft 成員可見）

問題4

You work with a team of researchers to develop state-of-the-art algorithms for financial analysis. Your team develops and debugs complex models in TensorFlow. You want to maintain the ease of debugging while also reducing the model training time. How should you set up your training environment?

A. Configure a v3-8 TPU VM SSH into the VM to tram and debug the model.

B. Configure a M-standard-4 VM with 4 NVIDIA P100 GPUs SSH into the VM and use Parameter Server Strategy to train the model.

C. Configure a M-standard-4 VM with 4 NVIDIA P100 GPUs SSH into the VM and use MultiWorkerMirroredStrategy to train the model.

D. Configure a v3-8 TPU node Use Cloud Shell to SSH into the Host VM to train and debug the model.

正確答案: A

說明：（僅 VCESoft 成員可見）

問題5

You are developing an ML model that uses sliced frames from video feed and creates bounding boxes around specific objects. You want to automate the following steps in your training pipeline: ingestion and preprocessing of data in Cloud Storage, followed by training and hyperparameter tuning of the object model using Vertex AI jobs, and finally deploying the model to an endpoint. You want to orchestrate the entire pipeline with minimal cluster management. What approach should you use?

A. Use Kubeflow Pipelines on Google Kubernetes Engine.

B. Use Vertex AI Pipelines with Kubeflow Pipelines SDK.

C. Use Vertex AI Pipelines with TensorFlow Extended (TFX) SDK.

D. Use Cloud Composer for the orchestration.

正確答案: C

說明：（僅 VCESoft 成員可見）

問題6

You are training a deep learning model for semantic image segmentation with reduced training time. While using a Deep Learning VM Image, you receive the following error: The resource ' projects/deeplearning- platforn/zones/europe-west4-c/acceleratorTypes/nvidia-tesla-k80 ' was not found. What should you do?

A. Ensure that you have GPU quota in the selected region.

B. Ensure that the required GPU is available in the selected region.

C. Ensure that you have preemptible GPU quota in the selected region.

D. Ensure that the selected GPU has enough GPU memory for the workload.

正確答案: B

說明：（僅 VCESoft 成員可見）

問題7

You are training models in Vertex Al by using data that spans across multiple Google Cloud Projects You need to find track, and compare the performance of the different versions of your models Which Google Cloud services should you include in your ML workflow?

A. Vertex Al Pipelines, Vertex Al Feature Store, and Vertex Al Experiments

B. Dataplex. Vertex Al Feature Store and Vertex Al TensorBoard

C. Vertex Al Pipelines: Vertex Al Experiments and Vertex Al Metadata

D. Dataplex. Vertex Al Experiments, and Vertex Al ML Metadata

正確答案: A

說明：（僅 VCESoft 成員可見）

問題8

You need to execute a batch prediction on 100 million records in a BigQuery table with a custom TensorFlow DNN regressor model, and then store the predicted results in a BigQuery table. You want to minimize the effort required to build this inference pipeline. What should you do?

A. Use the TensorFlow BigQuery reader to load the data, and use the BigQuery API to write the results to BigQuery.

B. Load the TensorFlow SavedModel in a Dataflow pipeline. Use the BigQuery I/O connector with a custom function to perform the inference within the pipeline, and write the results to BigQuery.

C. Create a Dataflow pipeline to convert the data in BigQuery to TFRecords. Run a batch inference on Vertex AI Prediction, and write the results to BigQuery.

D. Import the TensorFlow model with BigQuery ML, and run the ml.predict function.

正確答案: D

說明：（僅 VCESoft 成員可見）

問題9

You work for a pet food company that manages an online forum Customers upload photos of their pets on the forum to share with others About 20 photos are uploaded daily You want to automatically and in near real time detect whether each uploaded photo has an animal You want to prioritize time and minimize cost of your application development and deployment What should you do?

A. Download an object detection model from TensorFlow Hub. Deploy the model to a Vertex Al endpoint.
Send new user-submitted images to the model endpoint to classify whether each photo has an animal.

B. Send user-submitted images to the Cloud Vision API Use object localization to identify all objects in the image and compare the results against a list of animals.

C. Manually label previously submitted images as having animals or not Create an image dataset on Vertex Al Train a classification model by using Vertex AutoML to distinguish the two classes Deploy the model to a Vertex Al endpoint Send new user-submitted images to your model endpoint to classify whether each photo has an animal.

D. Manually label previously submitted images with bounding boxes around any animals Build an AutoML object detection model by using Vertex Al Deploy the model to a Vertex Al endpoint Send new user-submitted images to your model endpoint to detect whether each photo has an animal.

正確答案: B

說明：（僅 VCESoft 成員可見）

問題10

You work on the data science team for a multinational beverage company. You need to develop an ML model to predict the company's profitability for a new line of naturally flavored bottled waters in different locations.
You are provided with historical data that includes product types, product sales volumes, expenses, and profits for all regions. What should you use as the input and output for your model?

A. Use product type and the feature cross of latitude with longitude, followed by binning, as features. Use revenue and expenses as model outputs.

B. Use latitude, longitude, and product type as features. Use profit as model output.

C. Use product type and the feature cross of latitude with longitude, followed by binning, as features. Use profit as model output.

D. Use latitude, longitude, and product type as features. Use revenue and expenses as model outputs.

正確答案: C

說明：（僅 VCESoft 成員可見）

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