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PreFetching makes the processing faster because:
It compresses the dataset removing unnecessary features
Loads all the data to the RAM
Enables loading one batch at time leveraging multithreaded operations
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1 Loading and Preprocessing Data with TensorFlow - Loading and Preprocessing of Data - Part I
2 Loading and Preprocessing Data with TensorFlow - Loading and Preprocessing of Data - Part II
3 MCQ - Processing Data from the RAM is slower than processing from the Hard Disk
4 MCQ - Using Tensorflow Data API we can do the following
5 MCQ - TensorFlow Data API does not support text files
6 MCQ - The Tensorflow operation like repeat modifies the original dataset
7 MCQ - PreFetching makes the processing faster because
8 MCQ - TensorFlow Data API works only with a GPU
9 MCQ - TFRecords is a text format
10 MCQ - Protocol buffer is a format specifically to save images
11 MCQ - TFRecords are in binary as they are easier for a computer to partition, serialize and operate with
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