Google Exam Professional-Machine-Learning-Engineer Topic 1 Question 19 Discussion

Actual exam question for Google's Google Professional Machine Learning Engineer exam

Question #: 19
Topic #: 1

[All Google Professional Machine Learning Engineer Questions]

You have been asked to develop an input pipeline for an ML training model that processes images from disparate sources at a low latency. You discover that your input data does not fit in memory. How should you create a dataset following Google-recommended best practices?

ACreate a tf.data.Dataset.prefetch transformation

BConvert the images to tf .Tensor Objects, and then run Dataset. from_tensor_slices{).

CConvert the images to tf .Tensor Objects, and then run tf. data. Dataset. from_tensors ().

DConvert the images Into TFRecords, store the images in Cloud Storage, and then use the tf. data API to read the images for training

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Suggested Answer: B

by Haydee at May 09, 2022, 08:56 AM

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