Hands-On Deep Learning Algorithms with Python

Math operations in TensorFlow

Now, we will explore some of the operations in TensorFlow using the eager execution mode:

x = tf.constant([1., 2., 3.])y = tf.constant([3., 2., 1.])

Let's start with some basic arithmetic operations.

Use tf.add to add two numbers:

sum = tf.add(x,y)sum.numpy()array([4., 4., 4.], dtype=float32)

The tf.subtract function is used for finding the difference between two numbers:

difference = tf.subtract(x,y)difference.numpy()array([-2.,  0.,  2.], dtype=float32)

The tf.multiply function is used for multiplying two numbers:

product = tf.multiply(x,y)product.numpy()array([3., 4., 3.], dtype=float32)

Divide two numbers using tf.divide:

division = tf.divide(x,y)division.numpy()array([0.33333334, 1. , 3. ], dtype=float32) ...