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Explain data formats in tensorflow?
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Answer / Parul
TensorFlow supports various data formats including: tensors (1D, 2D, 3D), sparse tensors, and record readers. A tensor is a multi-dimensional array of numbers, while a sparse tensor represents an array with many zero or near-zero values. Record readers read datasets from files, and are particularly useful for large datasets that cannot be stored entirely in memory.
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