Update README.md

README.md

@@ -1,12 +1,18 @@
 # Machine-Learning-concepts
 This repository contains explanation for various Machine Learning and Deep Learning concepts with Python code implementations from scratch and/or using PyTorch.  
 
-# Non-Linearities  
+## Non-Linearities  
 - [ ] Sigmoid  
 - [ ] Tanh  
 - [ ] ReLU  
 
-# Losses  
+## Optimizers  
+- [ ] Stochastic Gradient Descent
+- [ ] Adam
+- [ ] AdaGrad
+- [ ] RMSprop
+
+## Losses  
 - [ ] Mean Squared Error Loss/ L2 Loss  
 - [ ] Mean Absolute Error/ L1 Loss  
 - [ ] Cross Entropy Loss  
@@ -18,13 +24,13 @@ This repository contains explanation for various Machine Learning and Deep Learn
 - [ ] Prototypical Loss  
 - [ ] Angular Prototypical Loss  
 
-# Architectures  
+## Architectures  
 - [ ] LeNet
 - [ ] AlexNet  
 - [ ] VGG-19  
 - [ ] ResNet-34  
 - [ ] ResNet-50  
 
-# Normalization
+## Normalization
 - [ ] Batch Normalization  
 - [ ] Layer Normalization