# Python TensorFlow matrix initialization and print

## Python TensorFlow Basic: Exercise-8 with Solution

Write a Python program that defines a TensorFlow variable to store a matrix of random values. Initialize and print the variable.

**Sample Solution:**

**Python Code:**

```
import tensorflow as tf
# Define the shape of the matrix
matrix_shape = (3, 3)
# Create a TensorFlow variable with random values
# Tensors are multi-dimensional arrays with a uniform type (called a dtype ).
random_matrix = tf.Variable(tf.random.normal(shape=matrix_shape))
# Print the initialized variable
print("Initialized Variable:")
print(random_matrix.numpy())
```

Output:

Initialized Variable: [[-0.580494 0.07652978 -0.5241451 ] [ 1.2946662 0.0206589 -1.4023237 ] [ 0.16084932 -1.0415876 1.2840588 ]]

**Explanation:**

In the exercise above -

- import tensorflow as tf - This line imports the TensorFlow library.
- matrix_shape = (3, 3) - Define the shape of the matrix.
- random_matrix = tf.Variable(tf.random.normal(shape=matrix_shape)) - Create a TensorFlow variable with random values.
- tf.random.normal(shape=matrix_shape) generates random values following a normal (Gaussian) distribution with the specified shape (in this case, a 3x3 matrix).
- tf.Variable() is used to create a TensorFlow variable that can be updated during training. We initialize it with the random values.
- print(random_matrix.numpy()) - Retrieve the values stored in the TensorFlow variable. In TensorFlow 2.x with eager execution, we can access the values directly using .numpy().

**Python Code Editor:**

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