Free Access Google.Professional-Machine-Learning-Engineer.v2024-09-13.q242 Practice Test (Page 39)

Question 186

One of your models is trained using data provided by a third-party data broker. The data broker does not reliably notify you of formatting changes in the dat a. You want to make your model training pipeline more robust to issues like this. What should you do?

A.Use tf.math to analyze the data, compute summary statistics, and flag statistical anomalies.

B.Use TensorFlow Transform to create a preprocessing component that will normalize data to the expected distribution, and replace values that don't match the schema with 0.

C.Use TensorFlow Data Validation to detect and flag schema anomalies.

D.Use custom TensorFlow functions at the start of your model training to detect and flag known formatting errors.

Question 187

You are working on a prototype of a text classification model in a managed Vertex AI Workbench notebook.
You want to quickly experiment with tokenizing text by using a Natural Language Toolkit (NLTK) library.
How should you add the library to your Jupyter kernel?

A.Install the NLTK library from a Jupyter cell by using the! pip install nltk -user command.

B.Write a custom Dataflow job that uses NLTK to tokenize your text and saves the output to Cloud Storage.

C.Create a new Vertex Al Workbench notebook with a custom image that includes the NLTK library.

D.Install the NLTK library from a terminal by using the pip install nltk command.

Question 188

You are working on a Neural Network-based project. The dataset provided to you has columns with different ranges. While preparing the data for model training, you discover that gradient optimization is having difficulty moving weights to a good solution. What should you do?

A.Use feature construction to combine the strongest features.

B.Use the representation transformation (normalization) technique.

C.Improve the data cleaning step by removing features with missing values.

D.Change the partitioning step to reduce the dimension of the test set and have a larger training set.

Question 189

While monitoring your model training's GPU utilization, you discover that you have a native synchronous implementation. The training data is split into multiple files. You want to reduce the execution time of your input pipeline. What should you do?

A.Increase the CPU load

B.Add caching to the pipeline

C.Increase the network bandwidth

D.Add parallel interleave to the pipeline

Question 190

You are deploying a new version of a model to a production Vertex Al endpoint that is serving traffic You plan to direct all user traffic to the new model You need to deploy the model with minimal disruption to your application What should you do?

A.1. Create a new endpoint.
2. Create a new model Set the parentModel parameter to the model ID of the currently deployed model and set it as the default version Upload the model to Vertex Al Model Registry
3. Deploy the new model to the new endpoint and set the new model to 100% of the traffic

B.1, Create a new model Set it as the default version Upload the model to Vertex Al Model Registry
2 Deploy the new model to the existing endpoint

C.1 Create a new model Set the parentModel parameter to the model ID of the currently deployed model Upload the model to Vertex Al Model Registry.
2 Deploy the new model to the existing endpoint and set the new model to 100% of the traffic.

D.1 Create a new endpoint.
2 Create a new model Set it as the default version Upload the model to Vertex Al Model Registry.
3. Deploy the new model to the new endpoint.
4 Update Cloud DNS to point to the new endpoint

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Question 186

Question 187

Question 188

Question 189

Question 190

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