Python Coding challenge - Day 409| What is the output of the following Python Code?

 

Code Explanation:

1. Importing TensorFlow

import tensorflow as tf

This line imports the TensorFlow library, a popular framework for machine learning and deep learning tasks.

tf is the alias used to refer to TensorFlow functions and modules.

2. Creating a Tensor

x = tf.constant([-1.0, 0.0, 1.0])

tf.constant() creates an immutable tensor (a multi-dimensional array) with the values [-1.0, 0.0, 1.0].

Tensors are similar to NumPy arrays and are the core data structure in TensorFlow.

3. Applying the Sigmoid Function

sigmoid = tf.nn.sigmoid(x)

tf.nn.sigmoid() applies the sigmoid activation function element-wise to the input tensor.

It squashes the input values to a range between 0 and 1, making it useful for binary classification tasks.

Applying to each input value:

4. Printing the Result

print(sigmoid)

This prints the output tensor containing the sigmoid values for each input.

The expected output will be:

[0.26894143 0.5 0.7310586]

TensorFlow may display it with additional information like data type (dtype) depending on the environment.

 Final Output

 [0.27, 0.5, 0.73]