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Google Professional Machine Learning Engineer Exam - Topic 1 Question 12 Discussion

Actual exam question for Google's Professional Machine Learning Engineer exam
Question #: 12
Topic #: 1
[All Professional Machine Learning Engineer Questions]

You are training a TensorFlow model on a structured data set with 100 billion records stored in several CSV files. You need to improve the input/output execution performance. What should you do?

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Suggested Answer: B

by Clorinda at May 07, 2022, 08:53 AM

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Eladia
4 months ago
Wait, can Bigtable really outperform BigQuery for this?
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Ressie
4 months ago
Definitely agree with using Cloud Storage for better performance!
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Carey
4 months ago
HDFS? Isn't that a bit outdated for this scale?
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Franklyn
4 months ago
I think TFRecords are the way to go for TensorFlow.
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Lasandra
5 months ago
BigQuery can handle massive datasets efficiently!
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Jenifer
5 months ago
I’m a bit confused about whether Cloud Bigtable would really improve performance compared to using TFRecords.
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Karrie
5 months ago
I practiced a similar question where we converted CSVs to TFRecords, and I think that’s definitely a good approach.
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Tequila
5 months ago
I think loading data into BigQuery could help, but I feel like it might not be the fastest option for such a large dataset.
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Adaline
5 months ago
I remember we discussed using TFRecords for better performance, but I'm not sure if Cloud Storage is better than HDFS for this case.
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Aide
5 months ago
Hmm, the continuation callouts could be an interesting approach, but I'm not sure if that would work well with the 3,000 concurrent users. Maybe we could look into using platform events and the empAPI instead?
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Reid
5 months ago
Hmm, I'm a bit unsure about this one. The question is asking about specific actions SoundCare should take, but I'm not totally clear on the details of the Federal Sentencing Guidelines. I'll need to review those closely.
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Roxanne
5 months ago
This question seems a bit concerning. I'll need to think carefully about the implications before answering.
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