Moved relu.py from maths/ to neural_network/activation_functions (#9753)

* Moved file relu.py from maths/ to neural_network/activation_functions

* Renamed relu.py to rectified_linear_unit.py

* Renamed relu.py to rectified_linear_unit.py in DIRECTORY.md

neural_network/activation_functions/rectified_linear_unit.py

@@ -0,0 +1,40 @@
+"""
+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)
+"""
+from __future__ import annotations
+
+import numpy as np
+
+
+def 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])
+    """
+
+    # compare two arrays and then return element-wise maxima.
+    return np.maximum(0, vector)
+
+
+if __name__ == "__main__":
+    print(np.array(relu([-1, 0, 5])))  # --> [0, 0, 5]