PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #64
PROFESSIONAL-MACHINE-LEARNING-ENGINEER Question #64: Real Exam Question with Answer & Explanation
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Question
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?
Options
- 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
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