Free PROFESSIONAL-MACHINE-LEARNING-ENGINEER Web TestEngine Demo

Exit VCEDump PROFESSIONAL-MACHINE-LEARNING-ENGINEER Professional Machine Learning Engineer

Q15 Single choice

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?

A
Create a tf.data.Dataset.prefetch transformation.
B
Convert the images to tf.Tensor objects, and then run Dataset.from_tensor_slices().
C
Convert the images to tf.Tensor objects, and then run tf.data.Dataset.from_tensors().
D
Convert the images into TFRecords, store the images in Cloud Storage, and then use the tf.data API to
read the images for training.

Previous Check answer

Question map15 / 44

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44

Current Correct Answered Incorrectly Reviewed 0 Remaining 44

Marked Questions0

No marked questions.

Answered Incorrectly0

No incorrect answers.

PROFESSIONAL-MACHINE-LEARNING-ENGINEER Web TestEngine demo