diff --git a/src/optimizer.py b/src/optimizer.py
new file mode 100644
index 0000000..504f631
--- /dev/null
+++ b/src/optimizer.py
@@ -0,0 +1,25 @@
+from abc import ABC, abstractmethod
+from enum import Enum
+from layer import Layer
+from neural_network import NeuralNetwork
+import numpy as np
+from loss import LossFunction
+
+
+class SGD:
+    __layers: list[Layer]
+    __loss_function: LossFunction
+
+    def __init__(self, layers: list[Layer], loss_function: LossFunction) -> None:
+        self.__layers = layers
+        self.__loss_function = loss_function
+
+    def train(self, output: np.ndarray, target: np.ndarray, lr=0.001):
+        """Forward needs to be called before this step"""
+        d_loss_wrt_output = self.__loss_function.get_diffrential(output=output, target=target)
+        for layer in self.__layers[::-1]:
+            d_loss_wrt_parameters = d_loss_wrt_output * layer.d_output_wrt_parameters()
+            delta_parameters = lr * d_loss_wrt_parameters
+            for i in range(len(delta_parameters)):
+                layer.parameters[i] -= delta_parameters[i]
+            d_loss_wrt_output = d_loss_wrt_output * layer.d_output_wrt_inputs()