January 2018
Intermediate to advanced
474 pages
10h 23m
English
Content preview from Mastering TensorFlow 1.x
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Tensors
Tensors are the basic elements of computation and a fundamental data structure in TensorFlow. Probably the only data structure that you need to learn to use TensorFlow. A tensor is an n-dimensional collection of data, identified by rank, shape, and type.
Rank is the number of dimensions of a tensor, and shape is the list denoting the size in each dimension. A tensor can have any number of dimensions. You may be already familiar with quantities that are a zero-dimensional collection (scalar), a one-dimensional collection (vector), a two-dimensional collection (matrix), and a multidimensional collection.
A scalar value is a tensor of rank 0 and thus has a shape of [1]. A vector or a one-dimensional array is a tensor of rank 1 and has ...
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