General changes, got basic visualization of an activation function working for a

convolutinoal layer.

manim_ml/neural_network/activation_functions/relu.py

@@ -0,0 +1,15 @@
+from manim import *
+
+from manim_ml.neural_network.activation_functions.activation_function import ActivationFunction
+
+class ReLUFunction(ActivationFunction):
+    """Rectified Linear Unit Activation Function"""
+
+    def __init__(self, function_name="ReLU", x_range=[-1, 1], y_range=[-1, 1]):
+        super().__init__(function_name, x_range, y_range)
+
+    def apply_function(self, x_val):
+        if x_val < 0:
+            return 0
+        else:
+            return x_val