L1 and L2 Regularization

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Good practices for addressing overfitting:

• add more data
• use Data Augmentation
• use batch normalization
• use architectures that generalize well
• reduce architecture complexity
• add Regularization
  • L1 and L2 Regularization - update the general cost function by adding another term known as the regularization term.
  • Dropout - at every iteration, it randomly selects some nodes and temporarily removes the nodes (along with all of their incoming and outgoing connections)
  • Data Augmentation
  • Early Stopping