A matrix is a two-dimensional array of numbers where each element is identified by two indices instead of just one. If a real matrix X has a height of m and a width of n, then we say that X ∈ Rm × n. Here, R is a set of real numbers.
The following example shows how different matrices are converted to tensor objects:
# convert matrices to tensor objectsimport numpy as npimport tensorflow as tf# create a 2x2 matrix in various formsmatrix1 = [[1.0, 2.0], [3.0, 40]]matrix2 = np.array([[1.0, 2.0], [3.0, 40]], dtype=np.float32)matrix3 = tf.constant([[1.0, 2.0], [3.0, 40]])print(type(matrix1))print(type(matrix2))print(type(matrix3))tensorForM1 = tf.convert_to_tensor(matrix1, dtype=tf.float32)tensorForM2 = tf.convert_to_tensor(matrix2, ...
