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Professional-Machine-Learning-Engineer PDF Exam (Downloadable)
Latest 2024 Syllabus Topics Included
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Updated : 10-Nov-2024
QA : 281 Answers With In-Depth Explanation
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Professional-Machine-Learning-Engineer Question and answers Include

Total Questions: 281 Q&A's
Single Choice: 277 Q&A's
Multiple Choice: 4 Q&A's

Google Professional-Machine-Learning-Engineer Exam Dumps - Valid Questions Answers

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Professional-Machine-Learning-Engineer Questions and Answers

Question # 1

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.

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.

B.

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.

C.

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.

D.

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.

Question # 2

You work at a bank You have a custom tabular ML model that was provided by the bank's vendor. The training data is not available due to its sensitivity. The model is packaged as a Vertex Al Model serving container which accepts a string as input for each prediction instance. In each string the feature values are separated by commas. You want to deploy this model to production for online predictions, and monitor the feature distribution over time with minimal effort What should you do?

A.

1 Upload the model to Vertex Al Model Registry and deploy the model to a Vertex Ai endpoint.

2. Create a Vertex Al Model Monitoring job with feature drift detection as the monitoring objective, and provide an instance schema.

B.

1 Upload the model to Vertex Al Model Registry and deploy the model to a Vertex Al endpoint.

2 Create a Vertex Al Model Monitoring job with feature skew detection as the monitoring objective and provide an instance schema.

C.

1 Refactor the serving container to accept key-value pairs as input format.

2. Upload the model to Vertex Al Model Registry and deploy the model to a Vertex Al endpoint.

3. Create a Vertex Al Model Monitoring job with feature drift detection as the monitoring objective.

D.

1 Refactor the serving container to accept key-value pairs as input format.

2 Upload the model to Vertex Al Model Registry and deploy the model to a Vertex Al endpoint.

3. Create a Vertex Al Model Monitoring job with feature skew detection as the monitoring objective.

Question # 3

You are the lead ML engineer on a mission-critical project that involves analyzing massive datasets using Apache Spark. You need to establish a robust environment that allows your team to rapidly prototype Spark models using Jupyter notebooks. What is the fastest way to achieve this?

A.

Configure a Compute Engine instance with Spark and use Jupyter notebooks.

B.

Set up a Dataproc cluster with Spark and use Jupyter notebooks.

C.

Set up a Vertex AI Workbench instance with a Spark kernel.

D.

Use Colab Enterprise with a Spark kernel.

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