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Free Professional Data Engineer Exam Braindumps (page: 34)

Page 34 of 68
PDF with 371 Questions

Your neural network model is taking days to train. You want to increase the training speed.
What can you do?

  1. Subsample your test dataset.
  2. Subsample your training dataset.
  3. Increase the number of input features to your model.
  4. Increase the number of layers in your neural network.

Answer(s): D


Reference:

https://towardsdatascience.com/how-to-increase-the-accuracy-of-a-neural-
network-9f5d1c6f407d



The marketing team at your organization provides regular updates of a segment of your customer dataset. The marketing team has given you a CSV with 1 million records that must be updated in BigQuery.
When you use the UPDATE statement in BigQuery, you receive a quotaExceeded error.
What should you do?

  1. Reduce the number of records updated each day to stay within the BigQuery UPDATE DML statement limit.
  2. Increase the BigQuery UPDATE DML statement limit in the Quota management section of the Google Cloud Platform Console.
  3. Split the source CSV file into smaller CSV files in Cloud Storage to reduce the number of BigQuery UPDATE DML statements per BigQuery job.
  4. Import the new records from the CSV file into a new BigQuery table. Create a BigQuery job that merges the new records with the existing records and writes the results to a new BigQuery table.

Answer(s): D



You work on a regression problem in a natural language processing domain, and you have 100M labeled exmaples in your dataset. You have randomly shuffled your data and split your dataset into train and test samples (in a 90/10 ratio). After you trained the neural network and evaluated your model on a test set, you discover that the root-mean-squared error (RMSE) of your model is twice as high on the train set as on the test set. How should you improve the performance of your model?

  1. Increase the share of the test sample in the train-test split.
  2. Try to collect more data and increase the size of your dataset.
  3. Try out regularization techniques (e.g., dropout of batch normalization) to avoid overfitting.
  4. Increase the complexity of your model by, e.g., introducing an additional layer or increase sizing the size of vocabularies or n-grams used.

Answer(s): D



You need to create a near real-time inventory dashboard that reads the main inventory tables in your BigQuery data warehouse. Historical inventory data is stored as inventory balances by item and location. You have several thousand updates to inventory every hour. You want to maximize performance of the dashboard and ensure that the data is accurate.
What should you do?

  1. Leverage BigQuery UPDATE statements to update the inventory balances as they are changing.
  2. Partition the inventory balance table by item to reduce the amount of data scanned with each inventory update.
  3. Use the BigQuery streaming the stream changes into a daily inventory movement table. Calculate balances in a view that joins it to the historical inventory balance table. Update the inventory balance table nightly.
  4. Use the BigQuery bulk loader to batch load inventory changes into a daily inventory movement table. Calculate balances in a view that joins it to the historical inventory balance table. Update the inventory balance table nightly.

Answer(s): A



Page 34 of 68



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madhan commented on June 16, 2023
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