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NEW QUESTION 50
You are creating a deep neural network classification model using a dataset with categorical input values. Certain columns have a cardinality greater than 10,000 unique values. How should you encode these categorical values as input into the model?

  • A. Convert the categorical string data to one-hot hash buckets.
  • B. Map the categorical variables into a vector of boolean values.
  • C. Convert each categorical value into a run-length encoded string.
  • D. Convert each categorical value into an integer value.

Answer: B

 

NEW QUESTION 51
You need to build classification workflows over several structured datasets currently stored in BigQuery. Because you will be performing the classification several times, you want to complete the following steps without writing code: exploratory data analysis, feature selection, model building, training, and hyperparameter tuning and serving. What should you do?

  • A. Run a BigQuery ML task to perform logistic regression for the classification
  • B. Use Al Platform Notebooks to run the classification model with pandas library
  • C. Use Al Platform to run the classification model job configured for hyperparameter tuning
  • D. Configure AutoML Tables to perform the classification task

Answer: D

Explanation:
https://cloud.google.com/automl-tables/docs/beginners-guide

 

NEW QUESTION 52
Your team is building an application for a global bank that will be used by millions of customers. You built a forecasting model that predicts customers1 account balances 3 days in the future. Your team will use the results in a new feature that will notify users when their account balance is likely to drop below $25. How should you serve your predictions?

  • A. 1. Create a Pub/Sub topic for each user
    2 Deploy a Cloud Function that sends a notification when your model predicts that a user's account balance will drop below the $25 threshold.
  • B. 1 Build a notification system on Firebase
  • C. 1. Create a Pub/Sub topic for each user
    2. Deploy an application on the App Engine standard environment that sends a notification when your model predicts that a user's account balance will drop below the $25 threshold
  • D. 1. Build a notification system on Firebase
    2. Register each user with a user ID on the Firebase Cloud Messaging server, which sends a notification when the average of all account balance predictions drops below the $25 threshold

Answer: B

Explanation:
2. Register each user with a user ID on the Firebase Cloud Messaging server, which sends a notification when your model predicts that a user's account balance will drop below the $25 threshold Explanation:
Firebase is designed for exactly this sort of scenario. Also, it would not be possible to create millions of pubsub topics due to GCP quotas https://cloud.google.com/pubsub/quotas#quotas
https://firebase.google.com/docs/cloud-messaging

 

NEW QUESTION 53
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