Welcome to the TensorFlow Tutorial!

In this tutorial, we will be covering the usage of the add function in TensorFlow.

The add function is used to add two tensors or constants in TensorFlow. It takes two input tensors or constants and returns their sum.

Example:

Let’s see an example of using the add function in TensorFlow:

import tensorflow as tf

# Create two constant tensors
a = tf.constant(5)
b = tf.constant(10)

# Add the tensors using the add function
sum = tf.add(a, b)

with tf.Session() as sess:
    result = sess.run(sum)
    print("The sum is:", result)

In this example, we create two constant tensors with values 5 and 10, and then use the add function to add them together. The result is then printed out.

Conclusion:

The add function in TensorFlow is a simple yet powerful function that allows you to perform addition operations on tensors and constants. It is a fundamental building block in creating more complex neural networks and machine learning models.

Thank you for reading this tutorial on the add function in TensorFlow. Stay tuned for more tutorials on TensorFlow and other machine learning topics!