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Exam Professional Machine Learning Engineer All Questions

View all questions & answers for the Professional Machine Learning Engineer exam

Exam Professional Machine Learning Engineer topic 1 question 29 discussion

Actual exam question from Google's Professional Machine Learning Engineer
Question #: 29
Topic #: 1
[All Professional Machine Learning Engineer Questions]

You have trained a model on a dataset that required computationally expensive preprocessing operations. You need to execute the same preprocessing at prediction time. You deployed the model on AI Platform for high-throughput online prediction. Which architecture should you use?

  • A. Validate the accuracy of the model that you trained on preprocessed data. Create a new model that uses the raw data and is available in real time. Deploy the new model onto AI Platform for online prediction.
  • B. Send incoming prediction requests to a Pub/Sub topic. Transform the incoming data using a Dataflow job. Submit a prediction request to AI Platform using the transformed data. Write the predictions to an outbound Pub/Sub queue.
  • C. Stream incoming prediction request data into Cloud Spanner. Create a view to abstract your preprocessing logic. Query the view every second for new records. Submit a prediction request to AI Platform using the transformed data. Write the predictions to an outbound Pub/Sub queue.
  • D. Send incoming prediction requests to a Pub/Sub topic. Set up a Cloud Function that is triggered when messages are published to the Pub/Sub topic. Implement your preprocessing logic in the Cloud Function. Submit a prediction request to AI Platform using the transformed data. Write the predictions to an outbound Pub/Sub queue.
Show Suggested Answer Hide Answer
Suggested Answer: B 🗳️

Comments

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SparkExpedition
Highly Voted 3 years, 4 months ago
Supporting B ..https://cloud.google.com/architecture/data-preprocessing-for-ml-with-tf-transform-pt1#where_to_do_preprocessing
upvoted 30 times
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inder0007
Highly Voted 3 years, 5 months ago
I think it should b B
upvoted 14 times
q4exam
3 years, 2 months ago
I also agree with B, this is how I would advise clients to do it as well
upvoted 4 times
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f084277
Most Recent 1 week, 3 days ago
Selected Answer: B
Dataflow is superior to Cloud Functions for doing data transformations at high volume. The answer is clearly B.
upvoted 2 times
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bludw
4 months, 4 weeks ago
Selected Answer: D
D. The issue with B is that DataFlow does not work well with high throughput
upvoted 1 times
f084277
1 week, 3 days ago
You are incorrect. Dataflow can handle MUCH higher volumes of data than Cloud Functions
upvoted 1 times
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desertlotus1211
1 month ago
Dataflow is ideal for handling computationally expensive preprocessing operations, as it scales automatically and can process the data in a distributed manner.
upvoted 1 times
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PhilipKoku
5 months, 2 weeks ago
Selected Answer: B
B) Pub/Sub + Dataflow
upvoted 1 times
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Liting
1 year, 4 months ago
Selected Answer: B
Went with B, using dataflow for large amount data transformation is the best option
upvoted 3 times
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SamuelTsch
1 year, 4 months ago
Selected Answer: B
I went to B. A is completely wrong. C: 1st cloud spanner is not designed for high throughput, also it is not for preprocessing. D: cloud function could not be get enough resource to do the high computational transformation.
upvoted 2 times
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ashu381
1 year, 5 months ago
Selected Answer: B
Because the concern here is high throughput and not specifically the latency so better to go with option B
upvoted 1 times
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Voyager2
1 year, 5 months ago
Selected Answer: D
B. Send incoming prediction requests to a Pub/Sub topic. Transform the incoming data using a Dataflow job. Submit a prediction request to AI Platform using the transformed data. Write the predictions to an outbound Pub/Sub queue https://dataintegration.info/building-streaming-data-pipelines-on-google-cloud
upvoted 1 times
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M25
1 year, 6 months ago
Selected Answer: B
Went with B
upvoted 1 times
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e707
1 year, 7 months ago
Selected Answer: D
I think it's D as B is not a good choice because it requires you to run a Dataflow job for each prediction request. This is inefficient and can lead to latency issues.
upvoted 3 times
f084277
1 week, 3 days ago
The question doesn't mention anything about latency
upvoted 1 times
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lucaluca1982
1 year, 6 months ago
Yes i agree Dataflow can introduce latency
upvoted 2 times
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lucaluca1982
1 year, 7 months ago
Selected Answer: D
I go for D. Option B has Dataflow that it is more suitable for batch
upvoted 1 times
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SergioRubiano
1 year, 8 months ago
Selected Answer: B
It's B
upvoted 1 times
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MithunDesai
1 year, 11 months ago
Selected Answer: B
yes ans B
upvoted 1 times
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hiromi
1 year, 11 months ago
Selected Answer: B
B Pubsub + DataFlow + Vertex AI (AI Platform)
upvoted 1 times
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suresh_vn
2 years, 3 months ago
Selected Answer: B
Should be B. Dataflow is BEST option for preprocessing training , testing data both
upvoted 2 times
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sachinxshrivastav
2 years, 3 months ago
Selected Answer: B
Answer should be B
upvoted 1 times
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Community vote distribution
A (35%)
C (25%)
B (20%)
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