neural_network.activation_functions.rectified_linear_unit
=========================================================

.. py:module:: neural_network.activation_functions.rectified_linear_unit

.. autoapi-nested-parse::

   This script demonstrates the implementation of the ReLU function.

   It's a kind of activation function defined as the positive part of its argument in the
   context of neural network.
   The function takes a vector of K real numbers as input and then argmax(x, 0).
   After through ReLU, the element of the vector always 0 or real number.

   Script inspired from its corresponding Wikipedia article
   https://en.wikipedia.org/wiki/Rectifier_(neural_networks)



Functions
---------

.. autoapisummary::

   neural_network.activation_functions.rectified_linear_unit.relu


Module Contents
---------------

.. py:function:: relu(vector: list[float])

   Implements the relu function

   Parameters:
       vector (np.array,list,tuple): A  numpy array of shape (1,n)
       consisting of real values or a similar list,tuple


   Returns:
       relu_vec (np.array): The input numpy array, after applying
       relu.

   >>> vec = np.array([-1, 0, 5])
   >>> relu(vec)
   array([0, 0, 5])