diff --git a/neural_network/activation_functions/binary_step.py b/neural_network/activation_functions/binary_step.py
new file mode 100644
index 000000000..8f8f4d405
--- /dev/null
+++ b/neural_network/activation_functions/binary_step.py
@@ -0,0 +1,36 @@
+"""
+This script demonstrates the implementation of the Binary Step function.
+
+It's an activation function in which the neuron is activated if the input is positive
+or 0, else it is deactivated
+
+It's a simple activation function which is mentioned in this wikipedia article:
+https://en.wikipedia.org/wiki/Activation_function
+"""
+
+
+import numpy as np
+
+
+def binary_step(vector: np.ndarray) -> np.ndarray:
+    """
+    Implements the binary step function
+
+    Parameters:
+        vector (ndarray): A vector that consists of numeric values
+
+    Returns:
+        vector (ndarray): Input vector after applying binary step function
+
+    >>> vector = np.array([-1.2, 0, 2, 1.45, -3.7, 0.3])
+    >>> binary_step(vector)
+    array([0, 1, 1, 1, 0, 1])
+    """
+
+    return np.where(vector >= 0, 1, 0)
+
+
+if __name__ == "__main__":
+    import doctest
+
+    doctest.testmod()