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Exam Professional Machine Learning Engineer topic 1 question 46 discussion

Actual exam question from Google's Professional Machine Learning Engineer
Question #: 46
Topic #: 1
[All Professional Machine Learning Engineer Questions]

As the lead ML Engineer for your company, you are responsible for building ML models to digitize scanned customer forms. You have developed a TensorFlow model that converts the scanned images into text and stores them in Cloud Storage. You need to use your ML model on the aggregated data collected at the end of each day with minimal manual intervention. What should you do?

  • A. Use the batch prediction functionality of AI Platform.
  • B. Create a serving pipeline in Compute Engine for prediction.
  • C. Use Cloud Functions for prediction each time a new data point is ingested.
  • D. Deploy the model on AI Platform and create a version of it for online inference.
Show Suggested Answer Hide Answer
Suggested Answer: A 🗳️
by Paul_Dirac at June 27, 2021, 1:20 a.m.

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Paul_Dirac
Highly Voted 3 years, 7 months ago
Use the model at the end of the day => Not D, C. Minimize manual intervention => not B Ans: A
upvoted 29 times
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PhilipKoku
Most Recent 8 months ago
Selected Answer: A
A) This a batch prediction using AI Platform
upvoted 1 times
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Arthurious
10 months, 2 weeks ago
Selected Answer: A
A is the most efficient
upvoted 1 times
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Sum_Sum
1 year, 2 months ago
Selected Answer: A
A is the only way
upvoted 1 times
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M25
1 year, 8 months ago
Selected Answer: A
Went with A
upvoted 1 times
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ares81
2 years, 1 month ago
Selected Answer: A
There is only A, for me.
upvoted 1 times
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koakande
2 years, 1 month ago
Selected Answer: A
Because aggregated data can be sent at the end of the day for batch prediction and AI platform is managed so satisfy minimal intervention requirement Not B as violates minimal intervention requirement Not C and D as real-time or online inference is not needed since data is aggregated at the end of the day
upvoted 3 times
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hiromi
2 years, 1 month ago
Selected Answer: A
You need to use your ML model on the aggregated data collected at the end of each day with minimal manual intervention.
upvoted 1 times
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seifou
2 years, 2 months ago
A. https://datatonic.com/insights/vertex-ai-improving-debugging-batch-prediction/#:~:text=Vertex%20AI%20Batch%20Prediction%20provides,to%20GCS%20or%20BigQuery%2C%20respectively.
upvoted 1 times
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Mohamed_Mossad
2 years, 7 months ago
Selected Answer: A
"You need to use your ML model on the aggregated data" that means we need the batch prediction feature in AI platform
upvoted 1 times
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ggorzki
3 years ago
Selected Answer: A
A https://cloud.google.com/ai-platform/prediction/docs/batch-predict
upvoted 3 times
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george_ognyanov
3 years, 4 months ago
Another vote for A. Technically, through the right lens D could be correct as well, but what tipped me towards A was batch vs online predictions and the need for less manual work.
upvoted 3 times
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Y2Data
3 years, 4 months ago
https://cloud.google.com/ai-platform/prediction/docs/batch-predict
upvoted 2 times
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Community vote distribution
A (35%)
C (25%)
B (20%)
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