Finally, we can perform the Forward Propagation for the whole network. First, we will prepare the input data, weights and biases so that they can be used in the process.

## Task 2

Variable X was set to only contain the feature data. What you need to do is to initiate the weights and biases with the values of your choice. Remember to create the arrays with proper shapes, provided in the code.

## Task 3

Once we have both types of layers, data and the weights, we can perform the Forward Propagation. Fill in the `forward_propagation`

function using the following flow: X -> hidden(`hidden_layer_fp`

) -> output(`output_layer_fp`

).

As usual, once your code is ready you can run it with the following command:

`python forward_propagation.py`