L1 and L2 Loss in Machine Learning
Overfitting is a phenomenon in which the model is trained too well over a specified data that it fails to recognize patterns outside the training set.
This can be optimized using different methods like:
* Weighted Regularization(L1 and L2)
* Activity Regularization
* Weight constraint
* Dropout
* Noise
* Stopping the training process by